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HandsOn Machine Learning with ScikitLearn, Keras, and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems,Used
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Through a series of recent 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 practical book shows you how.By using concrete examples, minimal theory, and two productionready Python frameworks??ScikitLearn and TensorFlow??author Aurlien Gron 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 linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you??ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use ScikitLearn to track an example machinelearning project endtoend Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
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This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What is the main focus of 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow'? A: The book focuses on providing practical guidance for implementing machine learning using Scikit-Learn and TensorFlow, emphasizing deep learning techniques and real-world applications.
- Q: Who is the author of this book? A: The author of 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow' is Aurélien Géron, a recognized expert in machine learning.
- Q: What prior knowledge is required to read this book? A: A basic understanding of programming is recommended, but no prior machine learning knowledge is necessary to get started.
- Q: What kind of exercises are included in the book? A: Each chapter includes practical exercises to reinforce learning, helping readers apply the concepts and techniques discussed.
- Q: How is the content structured in the book? A: The content is structured to progress from simple concepts like linear regression to more complex topics such as deep neural networks, ensuring a gradual learning curve.
- Q: Is this book suitable for beginners? A: Yes, it is designed for beginners who have programming experience, providing clear explanations and practical examples.
- Q: What tools and frameworks are covered in the book? A: The book covers Scikit-Learn and TensorFlow, two widely-used Python frameworks for machine learning and deep learning.
- Q: How many pages are in the book? A: The book contains 848 pages of content, making it a comprehensive resource for learning machine learning.
- Q: When was this book published? A: The book was published on November 5, 2019.
- Q: What edition of the book is available? A: This is the second edition of 'Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow'.