Tensorflow Deep Learning from Entry to Advanced

Name: Tensorflow Deep Learning from Entry to Advanced
Author: Edited by Zhang Defeng

TensorFlow深度学习从入门到进阶

by Edited by Zhang Defeng (张德丰编著)

Status: Completed
Source: Fanqie

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8.4Score

14Chapters

Synopsis

"TensorFlow Deep Learning from Entry to Advanced" uses TensorFlow as the main line to explain. Each chapter in the book is introduced with theory and ends with the consolidation of TensorFlow application. The combination of theory and practice allows readers to quickly master TensorFlow machine learning. "TensorFlow Deep Learning from Entry to Advanced" has 11 chapters, mainly including TensorFlow and deep networks, TensorFlow programming basics, TensorFlow programming advanced, linear regression, logistic regression, cluster analysis, neural network algorithms, convolutional neural networks, recurrent neural networks, other networks, comprehensive practical practice of machine learning, etc. "TensorFlow Deep Learning from Entry to Advanced" is suitable for TensorFlow beginners to read, and is also suitable for reference by researchers, scholars, and engineering technicians studying TensorFlow.

Reader comments

This book is great for TensorFlow beginners like me! The author Zhang Defeng's explanation is very clear, and the combination of theory and practice is also very helpful. The writing style is concise and clear, the writing style is smooth and easy to understand. The content in the book covers many machine learning topics from entry-level to advanced, and also includes comprehensive practical exercises, which is very practical! I think this book is a good helper for learning TensorFlow! 📖💪
2 likes2y ago

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