Machine learning with Python cookbook : Practical solutions from preprocessing to deep learning
- Mumbai: O'reilly: Shhroff Publishers and Distributors, c.2018.
- xiii+349p. : illustrations ; 24 cm.
This practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work
Vectors, matrices, and arrays -- Loading data -- Data wrangling -- Handling numerical data -- Handling categorical data -- Handling text -- Handling dates and times -- Handling images -- Dimensionality reduction using feature extraction -- Dimensionality reduction using feature selection -- Model evaluation -- Model selection -- Linear regression -- Trees and forests -- K-nearest neighbors -- Logistic regression -- Support vector machines -- Naive Bayes -- Clustering -- Neural networks -- Saving and loading trained models.
With Early Release ebooks, you get books in their earliest form--the author's raw and unedited content as he or she writes--so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters are available, and the final ebook bundle is released. The Python programming language and its libraries, including pandas and scikit-learn, provide a production-grade environment to help you accomplish a broad range of machine-learning tasks. With this comprehensive cookbook, data scientists and software engineers familiar with Python will benefit
978-93-5213-730-5
Machine learning. Python (Computer program language)