Cracking the Data Science Interview: 101+ Data Science Questions & Solutions

ISBN: 171068013X

Author: Lin, Maverick

Condition: New

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 Occams 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 bachelors 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.