The natural sequel to Volume One of the Crystal Ball Instruction Manual, this clean, readable text helps the new Data Science student further develop his or her data analysis and programming skills. The author brings his trademark conversational tone to the next steps of the discipline: synthetic data set generation, data fusion and reshaping, probabilistic reasoning and causality, accessing data from new sources (including JSON, relational databases, screen scraping, and public APIs) and the fundamental principles of machine learning. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.
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