About the Author
Aurélien Géron
ISBN 9789355421982
Rs. 5,200
O'Reilly Media
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow
Who it's for: Python developers and data scientists seeking practical ML skills
Authored by Aurélien Géron, Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow provides a practical guide to building intelligent systems. This third edition covers essential machine learning principles, deep learning advancements, reinforcement learning, and natural language processing, all implemented using Python libraries such as Scikit-Learn, Keras, and TensorFlow.Why You Should Read? Master practical machine learning techniques, from linear regression to deep learning. Implement robust neural networks and advanced models with TensorFlow and Keras. Gain hands-on experience applying ML principles to real-world datasets and model optimization. Explore modern deep learning architectures including CNNs, RNNs, and Transformers.
Highlights
- Third edition covering ML, deep learning, reinforcement learning, and NLP
- Hands-on examples using Scikit-Learn, Keras, and TensorFlow
- Includes modern architectures like CNNs, RNNs, and Transformers
- Focuses on real-world datasets and model optimization
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Sign inQuestions about this book
What does this book cover?
It covers essential machine learning principles, deep learning advancements, reinforcement learning, and natural language processing, with implementations using Scikit-Learn, Keras, and TensorFlow.
Is this book suitable for beginners?
It is practical and hands-on, but assumes some Python knowledge and familiarity with basic ML concepts. It is best for those with some programming experience.
What libraries are used?
The book uses Python libraries Scikit-Learn, Keras, and TensorFlow for implementing models.
Does it include deep learning architectures?
Yes, it covers modern deep learning architectures including CNNs, RNNs, and Transformers.
Is this the latest edition?
This is the third edition, which includes updates on deep learning and reinforcement learning.