Còn hàng
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition
Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition

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

Tình trạng: Còn hàng
Tác giả: O'Reilly
Loại: Artificial Intelligence

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition book assumes that you know close to nothing about Machine Learning. Its goal is to give you the concepts, tools, and intuition you need to implement programs capable of learning from data.

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📚📚 I. THÔNG TIN SẢN PHẨM
📒 Mã sản phẩm :  STT951
📒 Nhà xuất bản : O'Reilly Media; 3rd edition (November 8, 2022)
📒 Tác giả :  Hadley Wickham, Mine Çetinkaya-Rundel
📒 Ngôn ngữ :   Tiếng Anh
📒 ISBN      : 1098125975
📒 Số trang :  861  trang
📒 Hình thức : Bìa Mềm, IN ĐEN TRẮNG
📒 Loại : Sách gia công đóng gáy keo chắc chắn chất lượng cao
📒 Giấy in : Giấy ngoại định lượng 70msg, viết vẽ và hightlight thoải mái.
📒 Chất lượng : Bản in rõ nét, giá rất tốt cho mọi người.


📚📚 II. MÔ TẢ SẢN PHẨM
📒 1.Mô tả sản phẩm

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 bestselling 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 Aurélien Géron 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 ML 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, autoencoders, diffusion models, and transformers
• Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning


📒 2. Tác giả

Aurélien Géron is a Machine Learning consultant. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, a telecom consulting firm.


Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Société Générale), defense (Canada’s DOD), and healthcare (blood transfusion). He published a few technical books (on C++, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school.

 

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