{"product_id":"cracking-the-data-science-interview-101-data-science-questions-solutions-paperback","title":"Cracking the Data Science Interview: 101+ Data Science Questions \u0026 Solutions - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eMaverick Lin\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003cb\u003e \u003ci\u003e Cracking the Data Science Interview \u003c\/i\u003e \u003c\/b\u003e is the first book that attempts to capture the essence of data science in a concise, compact, and clean manner. In a \u003ci\u003e Cracking the Coding Interview\u003c\/i\u003e style, \u003cb\u003e \u003ci\u003e Cracking the Data Science Interview \u003c\/i\u003e \u003c\/b\u003e 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. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003eTopics include: \u003cbr\u003e - Necessary Prerequisites (statistics, probability, linear algebra, and computer science)\u003cbr\u003e - 18 Big Ideas in Data Science (such as Occam's Razor, Overfitting, Bias\/Variance Tradeoff, Cloud Computing, and Curse of Dimensionality)\u003cbr\u003e - Data Wrangling (exploratory data analysis, feature engineering, data cleaning and visualization)\u003cbr\u003e - Machine Learning Models (such as \u003ci\u003ek\u003c\/i\u003e-NN, random forests, boosting, neural networks, \u003ci\u003ek\u003c\/i\u003e-means clustering, PCA, and more)\u003cbr\u003e - Reinforcement Learning (Q-Learning and Deep Q-Learning)\u003cbr\u003e - Non-Machine Learning Tools (graph theory, ARIMA, linear programming)\u003cbr\u003e - Case Studies (a look at what data science means at companies like Amazon and Uber) \u003cp\u003e\u003c\/p\u003e 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 \u003ci\u003e Data Science Cheatsheet \u003c\/i\u003e and \u003ci\u003e Data Engineering Cheatsheet on GCP \u003c\/i\u003e and has previous experience in data science consulting for a Fortune 500 company focusing on fraud analytics.\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 120\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.28 x 8.5 x 5.51 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e December 17, 2019\u003c\/div\u003e\n            ","brand":"BooksCloud","offers":[{"title":"Default Title","offer_id":44839483834470,"sku":"9781710680133","price":23.83,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0599\/7255\/0758\/files\/bHJSQk5CSXRFWktMMkVKTUdZTnBLdz09.webp?v=1772506135","url":"https:\/\/infinitylightwa.com\/products\/cracking-the-data-science-interview-101-data-science-questions-solutions-paperback","provider":"Infinity Light","version":"1.0","type":"link"}