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دانلود کتاب Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition by Aurélien Géron

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.

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Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition by Aurélien Géron PDF

نویسنده: Aurélien Géron


پیش نمایش کتاب


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

نویسنده

Aurélien Géron

سال

2022

زبان

English

فرمت فایل

PDF + EPUB + AZW3

تعداد صفحات

895

ISBN10

1098125975

ISBN13

978-1098125974

Edition

3

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دانلود کتاب Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3rd Edition by Aurélien Géron

95,000تومان

نویسنده

Aurélien Géron

سال

2022

زبان

English

فرمت فایل

PDF + EPUB + AZW3

تعداد صفحات

895

ISBN10

1098125975

ISBN13

978-1098125974

Edition

3