內容簡介
內容簡介 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.
