Description: Machine Learning Pocket Reference : Working with Structured Data in Python, Paperback by Harrison, Matt, ISBN 1492047546, ISBN-13 9781492047544, Brand New, Free shipping in the US With detailed notes, tables, and examples, this handy reference will help you navigate the basics of structured machine learning. Author Matt Harrison delivers a valuable guide that you can use for additional support during training and as a convenient resource when you dive into your next machine learning project. Ideal for programmers, data scientists, and AI engineers, this book includes an overview of the machine learning process and walks you through classification with structured data. You'll also learn methods for clustering, predicting a continuous value (regression), and reducing dimensionality, among other topics. This pocket reference includes sections that cover:Classification, using the Titanic datasetCleaning data and dealing with missing dataExploratory data analysisCommon preprocessing steps using sample dataSelecting features useful to the modelModel selectionMetrics and classification evaluationRegression examples using k-nearest neighbor, decision trees, boosting, and moreMetrics for regression evaluationClusteringDimensionality reductionScikit-learn pipelines
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Book Title: Machine Learning Pocket Reference : Working with Structured Data
Number of Pages: 318 Pages
Publication Name: Machine Learning Pocket Référence : Working with Structured Data in Python
Language: English
Publisher: O'reilly Media, Incorporated
Item Height: 0.8 in
Publication Year: 2019
Subject: Data Modeling & Design, Intelligence (Ai) & Semantics, Data Processing, Programming Languages / Python
Type: Textbook
Item Weight: 7 Oz
Author: Matt Harrison
Item Length: 6.9 in
Subject Area: Computers
Item Width: 4.2 in
Format: Trade Paperback
