Ace the Data Science Interview - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Ace the Data Science Interview write by Kevin Huo. This book was released on 2021. Ace the Data Science Interview available in PDF, EPUB and Kindle.
Be the Outlier
Be the Outlier - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Be the Outlier write by Shrilata Murthy. This book was released on 2020-07-27. Be the Outlier available in PDF, EPUB and Kindle. 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.
RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More
RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More write by Zack Austin. This book was released on 2017-12-09. RocketPrep Ace Your Data Science Interview 300 Practice Questions and Answers: Machine Learning, Statistics, Databases and More available in PDF, EPUB and Kindle. 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.
Cracking the Data Science Interview
Cracking the Data Science Interview - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Cracking the Data Science Interview write by Maverick Lin. This book was released on 2019-12-17. Cracking the Data Science Interview available in PDF, EPUB and Kindle. 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.
Build a Career in Data Science
Build a Career in Data Science - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Build a Career in Data Science write by Emily Robinson. This book was released on 2020-03-24. Build a Career in Data Science available in PDF, EPUB and Kindle. 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
