Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

$49.00 $89.00
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

$49.00 $89.00
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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, 3rd Edition

Build practical machine learning and deep learning skills with Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow, Third Edition. Written for programmers who want to move from theory to implementation, this bestselling guide uses concrete examples, intuitive explanations, practical exercises, and production-ready Python frameworks to help you build intelligent systems from the ground up.

You don't need an advanced background in artificial intelligence or machine learning to get started. Programming experience is the primary prerequisite as author Aurélien Géron takes you from fundamental machine learning concepts to sophisticated neural network architectures.

Learn Machine Learning by Building Real Systems

The book begins with accessible techniques such as linear regression and gradually progresses toward modern deep learning. Throughout the process, practical code examples and exercises help reinforce concepts and turn theory into hands-on skills.

Explore Essential Machine Learning Techniques

You'll learn how to:

  • Use Scikit-Learn to develop a complete machine learning project from start to finish

  • Work with linear and nonlinear models

  • Build and evaluate support vector machines

  • Use decision trees and random forests

  • Apply ensemble learning methods

  • Improve models through practical machine learning workflows

  • Develop an intuitive understanding of how machine learning algorithms work

Discover Unsupervised Learning

Go beyond supervised learning and explore techniques that allow models to discover patterns in unlabeled data, including:

  • Dimensionality reduction

  • Clustering

  • Anomaly detection

  • Other practical unsupervised learning approaches

Dive Into Modern Neural Networks

The third edition takes you deep into the architectures and techniques powering today's AI applications. Explore:

  • Convolutional neural networks (CNNs)

  • Recurrent neural networks (RNNs)

  • Generative adversarial networks (GANs)

  • Autoencoders

  • Diffusion models

  • Transformer architectures

  • Modern deep learning workflows

Build AI Applications with TensorFlow and Keras

Learn how TensorFlow and Keras can be used to build, train, and deploy neural networks for a wide variety of applications, including:

  • Computer vision

  • Natural language processing

  • Generative AI

  • Deep reinforcement learning

  • Other intelligent applications

Learn Through Code, Examples, and Exercises

Rather than overwhelming readers with mathematical theory, Hands-On Machine Learning emphasizes intuitive understanding and practical implementation. Numerous examples and exercises give you opportunities to experiment with algorithms, train models, evaluate results, and develop your own machine learning solutions.

A Practical Path from Beginner to Advanced AI

Whether you're a software developer entering machine learning, a programmer exploring deep learning, or an aspiring AI engineer looking for a hands-on reference, this third edition provides a structured path from fundamental algorithms to advanced neural network architectures.

Learn the concepts. Write the code. Build machine learning models. Explore modern deep learning with Scikit-Learn, Keras, and TensorFlow.

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h
helan

This book provides a strong balance between machine learning theory and practical coding experience. It covers traditional machine learning techniques with Scikit-Learn before moving into neural networks and deep learning using Keras and TensorFlow. The step-by-step examples make complex topics easier to explore and provide opportunities to apply concepts directly through code. It is particularly useful for learners who want to move from understanding machine learning concepts to actually building working models.

z
zoran

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is an excellent practical resource for learning machine learning through coding and real-world examples. It explains algorithms and concepts clearly while giving readers hands-on experience with widely used Python tools. The progression from basic machine learning to deep learning makes it suitable for learners who want to build their skills step by step. A worthwhile book for aspiring data scientists, ML engineers, and Python developers.

H
Harry

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow is a comprehensive and practical guide for anyone looking to learn machine learning through hands-on experience. The book covers fundamental concepts as well as more advanced techniques, while providing practical examples that help readers understand how machine learning models are built and applied. The explanations of Scikit-Learn, Keras, and TensorFlow make it especially useful for readers who want to move from theory to implementation. Although some topics can be challenging for beginners, the step-by-step approach makes the learning process manageable. Overall, an excellent resource for students, developers, and aspiring machine learning practitioners who want to build a strong practical foundation.