Machine Learning in Action
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“Machine Learning in Action” is a unique book that blends the foundational theories of machine learning with the practical realities of building tools for everyday data analysis. In it, you will use the flexible Python programming language to build programs that implement algorithms for data classification, forecasting, recommendations, and higher-level features like summarization and simplification. As you work through the numerous examples, you will explore key topics like classification, numeric prediction, and clustering. Along the way, you will be introduced to important established algorithms, such as Apriori, through which you identify association patterns in large datasets and Adaboost, a meta-algorithm that can increase the efficiency of many machine learning tasks. · Classification · Forecasting Numeric Values with Regression · Unsupervised Learning · Additional Tools
Peter Harrington holds Bachelors and Masters Degrees in Electrical Engineering. He worked for Intel Corporation for seven years in California and China. Peter hold four US patents and his work has been published in two academic journals. He is actively involved with research on community detection and runs a software consulting business that focuses on scientific computing solutions.
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