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| ace the data science interview: Ace the Data Science Interview Kevin Huo, Nick Singh, 2021 |
| ace the data science interview: Be the Outlier Shrilata Murthy, 2020-07-27 According to LinkedIn's third annual U.S. Emerging Jobs Report, the data scientist role is ranked third among the top-15 emerging jobs in the U.S. Though the field of data science has been exploding, there didn't appear to be a comprehensive resource to help data scientists navigate the interview process... until now. In Be the Outlier: How to Ace Data Science Interviews, data scientist Shrilata Murthy covers all aspects of a data science interview in today's industry. Murthy combines her own experience in the job market with expert insight from data scientists with Google, Facebook, Amazon, NASA, Aetna, MBB & Big 4 consulting firms, and many more. In this book, you'll learn... the foundational knowledge that is key to any data science interview the 100-Word Story framework for writing a stellar resume what to expect from a variety of interview styles (take-home, presentation, case study, etc.), and actionable ways to differentiate yourself from your peers. By using real-world examples, practice questions, and sample interviews, Murthy has created an easy-to-follow guide that will help you crack any data science interview. After reading Be the Outlier, get ready to land your dream job in data science. |
| ace the data science interview: RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More Zack Austin, 2017-12-09 Here's what you get in this book: - 300 practice questions and answers spanning the breadth of topics under the data science umbrella - Covers statistics, machine learning, SQL, NoSQL, Hadoop and bioinformatics - Emphasis on real-world application with a chapter on Python libraries for machine learning - Focus on the most frequently asked interview questions. Avoid information overload - Compact format: easy to read, easy to carry, so you can study on-the-go Now, you finally have what you need to crush your data science interview, and land that dream job. About The Author Zack Austin has been building large scale enterprise systems for clients in the media, telecom, financial services and publishing since 2001. He is based in New York City. |
| ace the data science interview: Cracking the Data Science Interview Maverick Lin, 2019-12-17 Cracking the Data Science Interview is the first book that attempts to capture the essence of data science in a concise, compact, and clean manner. In a Cracking the Coding Interview style, Cracking the Data Science Interview first introduces the relevant concepts, then presents a series of interview questions to help you solidify your understanding and prepare you for your next interview. Topics include: - Necessary Prerequisites (statistics, probability, linear algebra, and computer science) - 18 Big Ideas in Data Science (such as Occam's Razor, Overfitting, Bias/Variance Tradeoff, Cloud Computing, and Curse of Dimensionality) - Data Wrangling (exploratory data analysis, feature engineering, data cleaning and visualization) - Machine Learning Models (such as k-NN, random forests, boosting, neural networks, k-means clustering, PCA, and more) - Reinforcement Learning (Q-Learning and Deep Q-Learning) - Non-Machine Learning Tools (graph theory, ARIMA, linear programming) - Case Studies (a look at what data science means at companies like Amazon and Uber) Maverick holds a bachelor's degree from the College of Engineering at Cornell University in operations research and information engineering (ORIE) and a minor in computer science. He is the author of the popular Data Science Cheatsheet and Data Engineering Cheatsheet on GCP and has previous experience in data science consulting for a Fortune 500 company focusing on fraud analytics. |
| ace the data science interview: Build a Career in Data Science Emily Robinson, Jacqueline Nolis, 2020-03-24 Summary You are going to need more than technical knowledge to succeed as a data scientist. Build a Career in Data Science teaches you what school leaves out, from how to land your first job to the lifecycle of a data science project, and even how to become a manager. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology What are the keys to a data scientist’s long-term success? Blending your technical know-how with the right “soft skills” turns out to be a central ingredient of a rewarding career. About the book Build a Career in Data Science is your guide to landing your first data science job and developing into a valued senior employee. By following clear and simple instructions, you’ll learn to craft an amazing resume and ace your interviews. In this demanding, rapidly changing field, it can be challenging to keep projects on track, adapt to company needs, and manage tricky stakeholders. You’ll love the insights on how to handle expectations, deal with failures, and plan your career path in the stories from seasoned data scientists included in the book. What's inside Creating a portfolio of data science projects Assessing and negotiating an offer Leaving gracefully and moving up the ladder Interviews with professional data scientists About the reader For readers who want to begin or advance a data science career. About the author Emily Robinson is a data scientist at Warby Parker. Jacqueline Nolis is a data science consultant and mentor. Table of Contents: PART 1 - GETTING STARTED WITH DATA SCIENCE 1. What is data science? 2. Data science companies 3. Getting the skills 4. Building a portfolio PART 2 - FINDING YOUR DATA SCIENCE JOB 5. The search: Identifying the right job for you 6. The application: Résumés and cover letters 7. The interview: What to expect and how to handle it 8. The offer: Knowing what to accept PART 3 - SETTLING INTO DATA SCIENCE 9. The first months on the job 10. Making an effective analysis 11. Deploying a model into production 12. Working with stakeholders PART 4 - GROWING IN YOUR DATA SCIENCE ROLE 13. When your data science project fails 14. Joining the data science community 15. Leaving your job gracefully 16. Moving up the ladder |
| ace the data science interview: Heard in Data Science Interviews Kal Mishra, 2018-10-03 A collection of over 650 actual Data Scientist/Machine Learning Engineer job interview questions along with their full answers, references, and useful tips |
| ace the data science interview: Doing Data Science Cathy O'Neil, Rachel Schutt, 2013-10-09 Now that people are aware that data can make the difference in an election or a business model, data science as an occupation is gaining ground. But how can you get started working in a wide-ranging, interdisciplinary field that’s so clouded in hype? This insightful book, based on Columbia University’s Introduction to Data Science class, tells you what you need to know. In many of these chapter-long lectures, data scientists from companies such as Google, Microsoft, and eBay share new algorithms, methods, and models by presenting case studies and the code they use. If you’re familiar with linear algebra, probability, and statistics, and have programming experience, this book is an ideal introduction to data science. Topics include: Statistical inference, exploratory data analysis, and the data science process Algorithms Spam filters, Naive Bayes, and data wrangling Logistic regression Financial modeling Recommendation engines and causality Data visualization Social networks and data journalism Data engineering, MapReduce, Pregel, and Hadoop Doing Data Science is collaboration between course instructor Rachel Schutt, Senior VP of Data Science at News Corp, and data science consultant Cathy O’Neil, a senior data scientist at Johnson Research Labs, who attended and blogged about the course. |
| ace the data science interview: Ace the Technical Interview Michael Rothstein, Daniel Rothstein, 2000-11-17 Land the job you want with this computer career guide--packed with interviewing techniques and thousands of answers to the toughest interview questions. Updated to cover new technologies for online jobs, SAP, Linux, Java servlets, and much more. Get the competitive edge in today's job market with this best-selling book! |
| ace the data science interview: Deep Learning Interviews Shlomo Kashani, 2020-12-09 The book's contents is a large inventory of numerous topics relevant to DL job interviews and graduate level exams. That places this work at the forefront of the growing trend in science to teach a core set of practical mathematical and computational skills. It is widely accepted that the training of every computer scientist must include the fundamental theorems of ML, and AI appears in the curriculum of nearly every university. This volume is designed as an excellent reference for graduates of such programs. |
| ace the data science interview: Data Science Interviews Exposed Jane You, Yanping Huang, Iris Wang, Feng Cao (Computer scientist), Ian Gao, 2015 The era has come when data science is changing the world and everyone's life. Data Science Interviews Exposed is the first book in the industry that covers everything you need to know to prepare for a data science career: from job market overview to job roles description, from resume preparation to soft skill development, and most importantly, the real interview questions and detailed answers. We hope this book can help the candidates in the data science job market, as well as those who need guidance to begin a data science career.--Back cover. |
| ace the data science interview: Ace the Programming Interview Edward Guiness, 2013-06-24 Be prepared to answer the most relevant interview questions and land the job Programmers are in demand, but to land the job, you must demonstrate knowledge of those things expected by today's employers. This guide sets you up for success. Not only does it provide 160 of the most commonly asked interview questions and model answers, but it also offers insight into the context and motivation of hiring managers in today's marketplace. Written by a veteran hiring manager, this book is a comprehensive guide for experienced and first-time programmers alike. Provides insight into what drives the recruitment process and how hiring managers think Covers both practical knowledge and recommendations for handling the interview process Features 160 actual interview questions, including some related to code samples that are available for download on a companion website Includes information on landing an interview, preparing a cheat-sheet for a phone interview, how to demonstrate your programming wisdom, and more Ace the Programming Interview, like the earlier Wiley bestseller Programming Interviews Exposed, helps you approach the job interview with the confidence that comes from being prepared. |
| ace the data science interview: Data Science and Machine Learning Dirk P. Kroese, Zdravko Botev, Thomas Taimre, Radislav Vaisman, 2019-11-20 Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code |
| ace the data science interview: Data Science with Machine Learning Narayanan Vishwanathan, 2019-09-20 Starts with statistics then goes towards Core Python followed by numpy to pandas to scipy and sklearnKey features Easy to learn, step by step explanation of examples. Questions related to core/basic Python, Excel, basic and advanced statistics are included. Covers numpy, scipy, sklearn and pandas to a greater detail with good number of examples Description The book e;Data science with Machine learning- Python interview questionse; is a true companion of people aspiring for data science and machine learning and provides answers to mostly asked questions in a easy to remember and presentable form.Data science is one of the hottest topics mainly because of the application areas it is involved and things which were once upon of time, impossible with earlier software has been made easy. This book is mainly intended to be used as last-minute revision, before interview, as all the important concepts have been given in simple and understand format. Many examples have been provided so that same can be used while giving answers in interview.This book tries to include various terminologies and logic used both as a part of Data Science and Machine learning for last minute revision. As such you can say that this book acts as a companion whenever you want to go for interview.Simple to use words have been used in the answers for the questions to help ease of remembering and representation of same. Examples where ever deemed necessary have been provided so that same can be used while giving answers in interview. Author tried to consolidate whatever he came across, on multiple interviews that he attended and put the same in words so that it becomes easy for the reader of the book to give direction on how the interview would be.With the number of data science jobs increasing, Author is sure that everyone who wants to pursue this field would like to keep this book as a constant companion. What will you learn You can learn the basic concept and terms related to Data Science You will get to learn how to program in python You can learn the basic questions of python programming By reading this book you can get to know the basics of Numpy You will get familiarity with the questions asked in interview related to Pandas. You will learn the concepts of Scipy, Matplotib, and Statistics with Excel Sheet Who this book is forThe book is intended for anyone wish to learn Python Data Science, Numpy, Pandas, Scipy, Matplotib and Statistics with Excel Sheet. This book content also covers the basic questions which are asked during an interview. This book is mainly intended to help people represent their answer in a sensible way to the interviewer. The answers have been carefully rendered in a way to make things quite simple and yet represent the seriousness and complexity of matter. Since data science is incomplete without mathematics we have also included a part of the book dedicated to statistics. Table of contents1. Data Science Basic Questions and Terms2. Python Programming Questions3. Numpy Interview Questions4. Pandas Interview Questions5. Scipy and its Applications6. Matplotlib Samples to Remember7. Statistics with Excel Sheet About the authorMr Vishwanathan has twenty years of hard code experience in software industry spanning across many multinational companies and domains. Playing with data to derive meaningful insights has been his domain and that is what took him towards data science and machine learning. |
| ace the data science interview: The Data Science Design Manual Steven S. Skiena, 2017-07-01 This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com) |
| ace the data science interview: Data Science For Dummies Lillian Pierson, 2021-08-20 Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today. |
| ace the data science interview: A Collection of Data Science Interview Questions Solved in Python and Spark Antonio Gulli, 2015-09-22 BigData and Machine Learning in Python and Spark |
| ace the data science interview: Cracking the Coding Interview Gayle Laakmann McDowell, 2011 Now in the 5th edition, Cracking the Coding Interview gives you the interview preparation you need to get the top software developer jobs. This book provides: 150 Programming Interview Questions and Solutions: From binary trees to binary search, this list of 150 questions includes the most common and most useful questions in data structures, algorithms, and knowledge based questions. 5 Algorithm Approaches: Stop being blind-sided by tough algorithm questions, and learn these five approaches to tackle the trickiest problems. Behind the Scenes of the interview processes at Google, Amazon, Microsoft, Facebook, Yahoo, and Apple: Learn what really goes on during your interview day and how decisions get made. Ten Mistakes Candidates Make -- And How to Avoid Them: Don't lose your dream job by making these common mistakes. Learn what many candidates do wrong, and how to avoid these issues. Steps to Prepare for Behavioral and Technical Questions: Stop meandering through an endless set of questions, while missing some of the most important preparation techniques. Follow these steps to more thoroughly prepare in less time. |
| ace the data science interview: Data Science from Scratch Joel Grus, 2015-04-14 Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases |
| ace the data science interview: Cracking The Machine Learning Interview Nitin Suri, 2018-12-18 A breakthrough in machine learning would be worth ten Microsofts. -Bill Gates Despite being one of the hottest disciplines in the Tech industry right now, Artificial Intelligence and Machine Learning remain a little elusive to most.The erratic availability of resources online makes it extremely challenging for us to delve deeper into these fields. Especially when gearing up for job interviews, most of us are at a loss due to the unavailability of a complete and uncondensed source of learning. Cracking the Machine Learning Interview Equips you with 225 of the best Machine Learning problems along with their solutions. Requires only a basic knowledge of fundamental mathematical and statistical concepts. Assists in learning the intricacies underlying Machine Learning concepts and algorithms suited to specific problems. Uniquely provides a manifold understanding of both statistical foundations and applied programming models for solving problems. Discusses key points and concrete tips for approaching real life system design problems and imparts the ability to apply them to your day to day work. This book covers all the major topics within Machine Learning which are frequently asked in the Interviews. These include: Supervised and Unsupervised Learning Classification and Regression Decision Trees Ensembles K-Nearest Neighbors Logistic Regression Support Vector Machines Neural Networks Regularization Clustering Dimensionality Reduction Feature Extraction Feature Engineering Model Evaluation Natural Language Processing Real life system design problems Mathematics and Statistics behind the Machine Learning Algorithms Various distributions and statistical tests This book can be used by students and professionals alike. It has been drafted in a way to benefit both, novices as well as individuals with substantial experience in Machine Learning. Following Cracking The Machine Learning Interview diligently would equip you to face any Machine Learning Interview. |
| ace the data science interview: Introduction to Data Science Rafael A. Irizarry, 2019-11-20 Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert. |
| ace the data science interview: Programming Interviews Exposed John Mongan, Noah Suojanen Kindler, Eric Giguère, 2018-04-17 Ace technical interviews with smart preparation Programming Interviews Exposed is the programmer’s ideal first choice for technical interview preparation. Updated to reflect changing techniques and trends, this new fourth edition provides insider guidance on the unique interview process that today's programmers face. Online coding contests are being used to screen candidate pools of thousands, take-home projects have become commonplace, and employers are even evaluating a candidate's public code repositories at GitHub—and with competition becoming increasingly fierce, programmers need to shape themselves into the ideal candidate well in advance of the interview. This book doesn't just give you a collection of questions and answers, it walks you through the process of coming up with the solution so you learn the skills and techniques to shine on whatever problems you’re given. This edition combines a thoroughly revised basis in classic questions involving fundamental data structures and algorithms with problems and step-by-step procedures for new topics including probability, data science, statistics, and machine learning which will help you fully prepare for whatever comes your way. Learn what the interviewer needs to hear to move you forward in the process Adopt an effective approach to phone screens with non-technical recruiters Examine common interview problems and tests with expert explanations Be ready to demonstrate your skills verbally, in contests, on GitHub, and more Technical jobs require the skillset, but you won’t get hired unless you are able to effectively and efficiently demonstrate that skillset under pressure, in competition with hundreds of others with the same background. Programming Interviews Exposed teaches you the interview skills you need to stand out as the best applicant to help you get the job you want. |
| ace the data science interview: Product Sense Peter Knudson, Braxton Bragg, 2021-07-12 Attempting to land a new job in product management is daunting. For starters, there have been no comprehensive blueprints for success. The interview process is grueling. Few candidates receive offers. Product Sense is the only comprehensive, yet accessible, resource available to help navigate a complex process and succeed an a hyper-competitive market. What will you learn from this book? The required PM common traits - ones that all PMs need to embody to get a job (regardless of industry, company, or product). The single, most crucial PM problem -What it is, why it is key to the role, and how to tackle it in four steps. Master our brand new Compass Framework - We designed our own proprietary interview framework from the ground up, which you can use to navigate product sense, execution, and leadership PM interview questions. How to get a job - A step-by-step hand-holding on what to do to land the most desired roles. Including take-home assignments, recruiter & hiring manager screens, and crafting your unique narrative - your PM Superpower. What's also inside? A detailed breakdown of the hiring criteria for PMs at FAANG and other tech companies Super-detailed example answers to tough PM interview case questions. An inside look at PM. Dozens of first-hand stories, interviews, real life examples, and no-fluff advice A robust glossary of PM terms used throughout the industry for easy reference This book will benefit those who are considering becoming PMs, those who are attempting to switch into product management from another role, or folks who are already PMs but want to be most prepared when applying for a new job. Here's what readers say about Product Sense: Product Sense helped me understand if PM is the right career path for me. Easy to read, clear, concise, and jam-packed full of insight and examples that illustrate all the concepts, this is the perfect starting point for anyone new to the field, and goes well beyond that for those looking to advance their career. Peter is one of the best strategic and tactical product minds I've ever worked with. For that reason, I'm not at all surprised that what he and Braxton have written here is a definitive guide to Product Management in today's ultra-competitive market. After reading Cracking the PM Interview, I was still lost as to how to structure my answers to case questions. While I understand that there is no right way to answer these interview questions, I appreciated that Product Sense gave me firm and clear guidance, walking me through the basics of PM thinking and how to adopt it in my interview answers. It was reassuring to see that the best mock interviews have all of the elements of Product Sense's Compass Framework. If CTPMI is the first step to prepare for landing a PM Role, then Product Sense is definitely the second step. |
| ace the data science interview: The Data Science Handbook Carl Shan, Henry Wang, William Chen, Max Song, 2015-05-03 The Data Science Handbook is a curated collection of 25 candid, honest and insightful interviews conducted with some of the world's top data scientists.In this book, you'll hear how the co-creator of the term 'data scientist' thinks about career and personal success. You'll hear from a young woman who created her own data scientist curriculum, subsequently landing her a role in the field. Readers of this book will be left with war stories, wisdom and |
| ace the data science interview: Quant Job Interview Questions and Answers Mark Joshi, Nick Denson, Nicholas Denson, Andrew Downes, 2013 The quant job market has never been tougher. Extensive preparation is essential. Expanding on the successful first edition, this second edition has been updated to reflect the latest questions asked. It now provides over 300 interview questions taken from actual interviews in the City and Wall Street. Each question comes with a full detailed solution, discussion of what the interviewer is seeking and possible follow-up questions. Topics covered include option pricing, probability, mathematics, numerical algorithms and C++, as well as a discussion of the interview process and the non-technical interview. All three authors have worked as quants and they have done many interviews from both sides of the desk. Mark Joshi has written many papers and books including the very successful introductory textbook, The Concepts and Practice of Mathematical Finance. |
| ace the data science interview: Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions Matt Taddy, 2019-08-23 Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling Understand how use ML tools in real world business problems, where causation matters more that correlation Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science. |
| ace the data science interview: Decode and Conquer Lewis C. Lin, 2013-11-28 Land that Dream Product Manager Job...TODAYSeeking a product management position?Get Decode and Conquer, the world's first book on preparing you for the product management (PM) interview. Author and professional interview coach, Lewis C. Lin provides you with an industry insider's perspective on how to conquer the most difficult PM interview questions. Decode and Conquer reveals: Frameworks for tackling product design and metrics questions, including the CIRCLES Method(tm), AARM Method(tm), and DIGS Method(tm) Biggest mistakes PM candidates make at the interview and how to avoid them Insider tips on just what interviewers are looking for and how to answer so they can't say NO to hiring you Sample answers for the most important PM interview questions Questions and answers covered in the book include: Design a new iPad app for Google Spreadsheet. Brainstorm as many algorithms as possible for recommending Twitter followers. You're the CEO of the Yellow Cab taxi service. How do you respond to Uber? You're part of the Google Search web spam team. How would you detect duplicate websites? The billboard industry is under monetized. How can Google create a new product or offering to address this? Get the Book that's Recommended by Executives from Google, Amazon, Microsoft, Oracle & VMWare...TODAY |
| ace the data science interview: Interview Hero Angela Guido, 2018-12-04 Are you tired of losing job offers at the interview stage? Sick of memorizing worn-out answer templates that make you feel like a fraud at best or a total douche at worst? Ready to start loving interviews instead of hating and fearing them?In this conversational and life-changing book, Angela Guido teaches you how to inspire people with your true story, ups and downs and all. While the other applicants will bore the interviewer to tears with their canned responses and pretense of perfection, you will entertain, engage, and connect. That will make you the most likeable candidate, the one your interviewer champions behind closed doors. Interview Hero teaches you¿¿New mindsets that transform interviews from painful interrogations to enjoyable conversations ¿Deep storytelling skills so you can relate your life's accomplishments as inspiring narratives without a trace of arrogance¿A step-by-step process to examine your experiences and construct your personal best answers to all the major interview question types ¿Techniques to build and maintain confidence before and during the interview so you can win the offerRemember, heroes aren't born heroes. They become heroes. Read on to become an Interview Hero today. |
| ace the data science interview: Machine Learning Bookcamp Alexey Grigorev, 2021-11-23 The only way to learn is to practice! In Machine Learning Bookcamp, you''ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image and text analysis, each new project builds on what you''ve learned in previous chapters. By the end of the bookcamp, you''ll have built a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. about the technology Machine learning is an analysis technique for predicting trends and relationships based on historical data. As ML has matured as a discipline, an established set of algorithms has emerged for tackling a wide range of analysis tasks in business and research. By practicing the most important algorithms and techniques, you can quickly gain a footing in this important area. Luckily, that''s exactly what you''ll be doing in Machine Learning Bookcamp. about the book In Machine Learning Bookcamp you''ll learn the essentials of machine learning by completing a carefully designed set of real-world projects. Beginning as a novice, you''ll start with the basic concepts of ML before tackling your first challenge: creating a car price predictor using linear regression algorithms. You''ll then advance through increasingly difficult projects, developing your skills to build a churn prediction application, a flight delay calculator, an image classifier, and more. When you''re done working through these fun and informative projects, you''ll have a comprehensive machine learning skill set you can apply to practical on-the-job problems. what''s inside Code fundamental ML algorithms from scratch Collect and clean data for training models Use popular Python tools, including NumPy, Pandas, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images and text Deploy ML models to a production-ready environment about the reader For readers with existing programming skills. No previous machine learning experience required. about the author Alexey Grigorev has more than ten years of experience as a software engineer, and has spent the last six years focused on machine learning. Currently, he works as a lead data scientist at the OLX Group, where he deals with content moderation and image models. He is the author of two other books on using Java for data science and TensorFlow for deep learning. |
| ace the data science interview: SQL Cookbook Anthony Molinaro, 2006 A guide to SQL covers such topics as retrieving records, metadata queries, working with strings, data arithmetic, date manipulation, reporting and warehousing, and hierarchical queries. |
| ace the data science interview: Ace the Trading Systems Developer Interview (C++ Edition) Dennis Thompson, 2020-08-06 Top 3 reasons why a software engineer might be interested to work at financial firms in the capital markets area 1) work with top Hedge Funds, Investment Banks, HFT firms, Algorithmic Trading firms, Exchanges, etc. 2) implement smart algorithms and build low-latency, high-performance and mission-critical software with talented engineers 3) earn top compensation This book will help you with interview preparation for landing high-paying software engineering jobs in the financial markets industry – Hedge Funds, Banks, Algo Trading firms, HFT firms, Exchanges, etc. This book contains 120+ questions with solutions/answers fully explained. Covers all topics in breadth and depth. Questions that are comparable difficulty level to those asked at top financial firms. Resources are provided to help you fill your gaps. Who this book is for: 1)This book is written to help software developers who want to get into the financial markets/trading industry as trading systems developers operating in algorithmic trading, high-frequency trading, market-making, electronic trading, brokerages, exchanges, hedge funds, investment banks, and proprietary trading firms. You can work across firms involved in various asset classes such as equities, derivatives, FX, bonds, commodities, and cryptocurrencies, among others. 2)This book serves the best for programmers who already know C++ or who are willing to learn C++. Due to the level of performance expected from these systems, most trading systems are developed in C++. 3) This book can help you improve upon the skills necessary to get into prestigious, high paying tech jobs at financial firms. Resources are provided. Practice questions and answers help you to understand the level and type of questions expected in the interview. What does this book contain: 1)Overview of the financial markets trading industry – types of firms, types of jobs, work environment and culture, compensation, methods to get job interviews, etc. 2)For every chapter, a guideline of what kind of topics are asked in the interviews is mentioned. 3)For every chapter, many questions with full solutions/answers are provided. These are of similar difficulty as those in real interviews, with sufficient breadth and depth. 4)Topics covered – C++, Multithreading, Inter-Process Communication, Network Programming, Lock-free programming, Low Latency Programming and Techniques, Systems Design, Design Patterns, Coding Questions, Math Puzzles, Domain-Specific Tools, Domain Knowledge, and Behavioral Interview. 5)Resources – a list of books for in-depth knowledge. 6) FAQ section related to the career of software engineers in tech/quant financial firms. Upsides of working as Trading Systems Developer at top financial firms: 1)Opportunity to work on cutting-edge technologies. 2)Opportunity to work with quants, traders, and financial engineers to expand your qualitative and quantitative understanding of the financial markets. 3)Opportunity to work with other smart engineers, as these firms tend to hire engineers with a strong engineering caliber. 4)Top compensation with a big base salary and bonus, comparable to those of FAANG companies. 5)Opportunity to move into quant and trader roles for the interested and motivated. This book will be your guideline, seriously cut down your interview preparation time, and give you a huge advantage in landing jobs at top tech/quant firms in finance. Book website: www.tradingsystemsengineer.com |
| ace the data science interview: Becoming a Data Head Alex J. Gutman, Jordan Goldmeier, 2021-04-13 Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful. Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data—now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you. |
| ace the data science interview: The Everything Practice Interview Book Dawn Rosenberg McKay, 2009-03-18 Being highly qualified for a job isn't enough to get the competitive edge in today's job market - a candidate needs to ace the interview as well. Career planning expert Dawn Rosenberg McKay gives you the best answers to more than 200 of the toughest interview questions, such as: What are your long-term goals? How do you handle failure? What does success mean to you? Why did you leave your last job? From preparing for the first interview to polishing existing skills, this book arms you with the knowledge of what to say and how to say it, giving you the advantage over competitors and the confidence to succeed. |
| ace the data science interview: Experiential Learning David A. Kolb, 2015 Experiential learning is a powerful and proven approach to teaching and learning that is based on one incontrovertible reality: people learn best through experience. Now, in this extensively updated book, David A. Kolb offers a systematic and up-to-date statement of the theory of experiential learning and its modern applications to education, work, and adult development. Experiential Learning, Second Edition builds on the intellectual origins of experiential learning as defined by figures such as John Dewey, Kurt Lewin, Jean Piaget, and L.S. Vygotsky, while also reflecting three full decades of research and practice since the classic first edition. Kolb models the underlying structures of the learning process based on the latest insights in psychology, philosophy, and physiology. Building on his comprehensive structural model, he offers an exceptionally useful typology of individual learning styles and corresponding structures of knowledge in different academic disciplines and careers. Kolb also applies experiential learning to higher education and lifelong learning, especially with regard to adult education. This edition reviews recent applications and uses of experiential learning, updates Kolb's framework to address the current organizational and educational landscape, and features current examples of experiential learning both in the field and in the classroom. It will be an indispensable resource for everyone who wants to promote more effective learning: in higher education, training, organizational development, lifelong learning environments, and online. |
| ace the data science interview: Sworn by Blood J.R. Pearse Nelson, 2019-08-11 The half-human daughter of a love god. The fae heir to a powerful destiny. And the aphrodisiac expected to save Underworld from disaster. Hazel can’t help what she is. Being the daughter of a love god isn’t all fun and games. She wants no part of her father’s world. Otherworld forests are full of huge, scary creatures and annoying pixie pests. And the people there are no better…they’ve never even given her a chance. She wants nothing to do with Sidhe men, either. Especially after that last time… But her effect on human men (and women, for that matter) makes a normal relationship impossible, not to mention introducing some seriously awkward situations. Ian has spent the last year on a fruitless mission to fulfill a family obligation set long, long before his time. All he’s found is trouble. Now he needs the love god’s help to see the end of this task and get back home. Until then, he’s stuck beyond the veil in the human world, while plots against his future rule thicken back in Underworld. What better way to bargain with a love god than through his daughter? But Hazel won’t be a pawn in Sidhe games. And Ian must make peace with his family’s legacy; he must do it soon. Somehow, they’ll have to work together, before time runs out. Sworn by Blood is the first novel in the Of the Blood fantasy romance series, which is now complete and includes the following books: Sworn by Blood The Risen Goddess Darkest Skies Sacred Guardian Shield in Shadows Search terms: fantasy romance, paranormal romance, PNR, magic, fantasy love, love, fae, sidhe, portal, otherworld, underworld, celtic, faery, gods, goddesses, pixie dust, myth, myths, adventure, romance, romance ebook, romance novel, romance series |
| ace the data science interview: Ace Your Teacher Interview Anthony D. Fredericks, 2016 Annotation It's a question that's asked thousands of times by thousands of potential teachers every year. In this captivating and highly practical book, (which builds on the success of the critically acclaimed Ace Your Teacher Interview) award-winning author and teacher, Anthony D. Fredericks offers real-world guidelines, fresh advice, and down-to-earth tips from numerous principals and superintendents around the country. Most important, he provides you with insider knowledge what types of vocabulary and key words/phrases that school administrators look for. Discover what's often missing from teacher resumes and what things to exclude from your resume.Ace Your Teacher Resume (& Cover Letter) gives you proven strategies, winning guidelines, along with scores of sample resumes and cover letters. Also included are step-by-step writing instructions and that help you rise to the top of the applicant pool and give you a distinctive advantage over the competition - an advantage that can result in a permanent job offer and the career of your dreams. With this step-by-step guide, you can create a dynamic resume, with a catching objective, and an incredible cover letter, all rooted in your own unique experiences and philosophy, and sure to impress any potential interviewer. This book will show you how you can stand out as a teacher candidate truly at the top of your game! |
| ace the data science interview: The Boston Consulting Group on Strategy Carl W. Stern, Michael S. Deimler, 2012-06-14 A collection of the best thinking from one of the most innovative management consulting firms in the world For more than forty years, The Boston Consulting Group has been shaping strategic thinking in business. The Boston Consulting Group on Strategy offers a broad and up-to-date selection of the firm's best ideas on strategy with fresh ideas, insights, and practical lessons for managers, executives, and entrepreneurs in every industry. Here's a sampling of the provocative thinking you'll find inside: You have to be the scientist of your own life and be astonished four times:at what is, what always has been, what once was, and what could be. The majority of products in most companies are cash traps . . . .[They] are not only worthless, but a perpetual drain on corporate resources. Use more debt than your competition or get out of the business. When information flows freely, reputation, more than reciprocity,becomes the basis for trust. As a strategic weapon, time is the equivalent of money, productivity,quality, even innovation. When brands become business systems, brand management becomes far too important to leave to the marketing department. The winning organization of the future will look more like a collection ofjazz ensembles than a symphony orchestra. Most of our organizations today derive from a model whose original purpose was to control creativity. Rather than being an obstacle, uncertainty is the very engine of transformation in a business, a continuous source of new opportunities. IP assets lack clear property lines. Every bit of intellectual property you can own comes with connections to other valuable innovations. |
| ace the data science interview: How Smart Machines Think Sean Gerrish, 2018-10-30 Everything you've always wanted to know about self-driving cars, Netflix recommendations, IBM's Watson, and video game-playing computer programs. The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM's Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these things work? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today's machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine (which had an unexpected ending); and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. He explains how artificial neural networks enable computers to perceive the world—and to play Atari video games better than humans. He explains Watson's famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. Computers have not yet mastered everything, however; Gerrish outlines the difficulties in creating intelligent agents that can successfully play video games like StarCraft that have evaded solution—at least for now. Gerrish weaves the stories behind these breakthroughs into the narrative, introducing readers to many of the researchers involved, and keeping technical details to a minimum. Science and technology buffs will find this book an essential guide to a future in which machines can outsmart people. |
| ace the data science interview: Science of Selenium Kalilur Rahman, 2019-12-10 Step-by-step guide to understand key concepts for Selenium Automation using examples to shine in your interview for test automation roles DESCRIPTION Software Engineering has taken massive strides with a multitude of technology innovations. With several changes being introduced Ð development of products and their integration into the market Ð understanding of mobile devices and user interface channels across a plethora of platforms is getting complex day by day. In addition, since the process or procedures of software testing for products and applications can become an act of boiling the ocean, the role of test automation is crucial while dealing with such challenges. This book aims to equip you with just enough knowledge of Selenium in conjunction with concepts you need to master to succeed in the role of Selenium Automation Engineer. It is the most widely used test automation tool and a much sought-after automated testing suite, by automation engineers who are equipped with technical expertise and analytical skills, for web applications across different browsers and platforms.ÊÊ The book starts with a brief introduction to the world of automation and why it is important, succinctly covering the history of Selenium and the capabilities it offers. In this book, you will learn how to do simple Selenium-based automation with examples and understand the progressive complexity of some key features. Before diving deep into advanced concepts such as Page Object Models, Test Automation Framework and Cross Browser testing, you will grasp comprehensive knowledge of several concepts related to Java, Python, JavaScript and Ruby programming languages. In addition, concepts on Selenium Web Driver, Grid and use of Selenium Locators, IDEs and tools to build complex test automation framework are also explained with practical examples. Each chapter has a set of key concepts and questions that one may face during interviews.Ê KEY FEATURES Acquire Selenium skills to do independent test automation projects Learn the basics of Selenium Web Driver for test automation using Selenium Understand Page Object Model, including how and when they're used in test automation Understand the approach for building a test automation framework Build Selenium test automation scripts using various languages Ð Java, Python, JavaScript/Node JS and Ruby Learn how to report and integrate with CI tools for test automationÊ Get some professional tips for handing interviews and test automation approach Implement cross-browser testing scenarios using Selenium Grid and commercial tools and services WHAT WILL YOU LEARN By the end of the book, you will find several examples to help ignite your understanding and usage of Selenium across a myriad of languages and frameworks. With this, youÕll be able to put your knowledge to practice and solve real-life test automation challenges such as testing a web site, mobile application and leveraging tools available for fast-tracking your test automation approach. You can also choose to practice additional examples provided in the code bundle of the book to master the concepts and techniques explained in this book. WHO THIS BOOK IS FOR The book is intended for anyone looking to make a career in test automation using Selenium, all aspiring manual testers who want to learn the most powerful test automation framework Ð Selenium and associated programming languages Ð or working professionals who want to switch their career to testing. While no prior knowledge of Selenium, test automation or related technologies is assumed, it will be helpful to have some programming experience to understand the concepts explained in this book.Ê Table of Contents 1. Introduction to Test Automation 2. Introduction to SeleniumÊ 3. Understanding Selenium Architecture 4. Understanding Selenium Tools 5. Understanding Web UIÊ 6. Web UI Automation with Selenium Using Java & Python 7. Selenium Coding with Other Languages Ð Ruby & JavaScript 8. Building a Test Automation Framework with Selenium 9. Advanced Features of Selenium Using Java & Python 10. Cross-Browser Test Automation 11. Tips and Tricks for Test Automation 12. Interview Tips |
| ace the data science interview: Deep Learning and the Game of Go Kevin Ferguson, Max Pumperla, 2019-01-06 Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning |
| ace the data science interview: Cracking the PM Interview Gayle Laakmann McDowell, Jackie Bavaro, 2013 How many pizzas are delivered in Manhattan? How do you design an alarm clock for the blind? What is your favorite piece of software and why? How would you launch a video rental service in India? This book will teach you how to answer these questions and more. Cracking the PM Interview is a comprehensive book about landing a product management role in a startup or bigger tech company. Learn how the ambiguously-named PM (product manager / program manager) role varies across companies, what experience you need, how to make your existing experience translate, what a great PM resume and cover letter look like, and finally, how to master the interview: estimation questions, behavioral questions, case questions, product questions, technical questions, and the super important pitch. |
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