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Machine learning

Tác giả: Jason Bell

Dig deep into the data with a hands-on guide to machine learning Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals.

Hands-on gradient boosting with XGBoost and scikit-learn : perform accessible machine learning and extreme gradient boosting with python

Tác giả: Corey Wade

The book introduces machine learning and XGBoost in scikit-learn before building up to the theory behind gradient boosting. You'll cover decision trees and analyze bagging in the machine learning context, learning hyperparameters that extend to XGBoost along the way. You'll build gradient boosting...

Hands-On machine learning with scikit-learn, keras, and tensorFlow : concepts, tools, and techniques to build intelligent systems : 2nd ed

Tác giả: Aurélien Géron

By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple...

Deep learning

Tác giả: Ian Goodfellow, Yoshua Bengio, and Aaron Courville

The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks,...

Machine learning

Tác giả: Tom M Mitchell

Contents: 1. Introduction; 2. Concept learning and the general-to-specific ordering; 3. Decision tree learning; 4. Artificial neural networks; 5. Evaluating hypotheses; 6. Bayesian learning; 7. Computational learning theory; 8. Instance-based learning; 9. Genetic algorithms; 10. Learning sets of...