[ FreeCourseWeb ] Cracking the Data Science Interview - 101 + Data Science Questions & Solutions

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[ FreeCourseWeb.com ] Cracking the Data Science Interview: 101+ Data Science Questions & Solutions

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English | 2019 | ASIN: B082T29SQB | 119 Pages | PDF | 0.9 MB

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)

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[ FreeCourseWeb ] Cracking the Data Science Interview - 101 + Data Science Questions & Solutions


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