Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e : Concepts, Tools, and Techniques to Build Intelligent Systems - Aurelien Geron
eTextbook alternate format product

Instant online reading.

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e

Concepts, Tools, and Techniques to Build Intelligent Systems

By: Aurelien Geron

Paperback | 18 October 2022 | Edition Number 3

At a Glance

Paperback


RRP $171.00

$82.95

51%OFF

or 4 interest-free payments of $20.74 with

 or 
In Stock and Aims to ship in 1-2 business days

Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use scikit-learn to track an example machine learning project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning Train neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI

More in Natural Language & Machine Translation

AI Engineering : Building Applications with Foundation Models - Chip Huyen
Think Python : How To Think Like a Computer Scientist - Allen B. Downey
Designing Large Language Model Applications : A Holistic Approach - Suhas Pai
Machine Translation and Translation Theory - Omri Asscher
AI and Ada : Artificial Translation and Creation of Literature - Mark Seligman