Mastering Machine Learning With Scikit-learn 2nd Ed (Packt)
Mastering Machine Learning With Scikit-learn 2nd Ed (Packt)
Wednesday, 17 January 2018

Now in its second edition of this book shows how the algorithms and techniques offered by machine learning can be used to automate any analytical model. Author Gavin Hackeling examines a variety of machine learning models including popular machine learning algorithms including k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods.

<ASIN:1788299876>

The book shows how to build systems that classify documents, recognize images, detect ads, and more. It also covers scikit-learn’s API for extracting features from categorical variables, text and images and evaluating model performance.

Author: Gavin Hackeling
Publisher: Packt Publishing
Date: July 2017
Pages: 254
ISBN: 978-1788299879
Print: 1788299876
Kindle: B06ZYRPFMZ
Audience: developers interested in machine learning
Level: Intermediate
Category: Artificial Intelligence

Topics covered include

  • Review fundamental concepts such as bias and variance
  • Extract features from categorical variables, text, and images
  • Predict the values of continuous variables using linear regression and K Nearest Neighbors
  • Classify documents and images using logistic regression and support vector machines
  • Create ensembles of estimators using bagging and boosting techniques
  • Discover hidden structures in data using K-Means clustering
  • Evaluate the performance of machine learning systems in common tasks

Book Watch is I Programmer's listing of new books and is compiled using publishers' publicity material. It is not to be read as a review where we provide an independent assessment. Some, but by no means all, of the books in Book Watch are eventually reviewed.

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