
Author | : Kevin Huo |
Publisher | : Unknown |
File Size | : 45,5 Mb |
Release Date | : 23 September 2023 |
ISBN | : 0578973839 |
Pages | : 290 pages |
Rating | : /5 ( users) |
This is popular Big data book PDF by Kevin Huo and published on 23 September 2023 by Unknown. Ace the Data Science Interview book is available to download in pdf, epub and kindle format with total pages 290. Read online book directly from your device by click download button. You can see detail book and summary of Ace the Data Science Interview book below. Enjoy the book and thanks for visiting us.
Author | : Kevin Huo |
Publisher | : Unknown |
File Size | : 45,5 Mb |
Release Date | : 23 September 2023 |
ISBN | : 0578973839 |
Pages | : 290 pages |
Rating | : /5 ( users) |
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
Get BookAccording 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
Get BookHere'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
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Get BookA collection of over 650 actual Data Scientist/Machine Learning Engineer job interview questions along with their full answers, references, and useful tips
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Get BookThink about your data intelligently and ask the right questions Key FeaturesMaster data cleaning techniques necessary to perform real-world data science and machine learning tasksSpot common problems with dirty data and develop flexible solutions from first principlesTest and refine your newly acquired skills through detailed exercises at the end of
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