Deep Learning with Python pdf epub mobi txt 電子書 下載2025
- 深度學習
- Python
- 機器學習
- 人工智能
- Keras
- DeepLearning
- 計算機
- 編程
- Deep Learning
- Python
- Machine Learning
- Neural Networks
- Data Science
- Artificial Intelligence
- TensorFlow
- Keras
- Programming
具體描述
Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects.
著者簡介
François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
圖書目錄
1.What is deep learning?
2.Before we begin: the mathematical building blocks of neural networks
3.Getting started with neural networks
4.Fundamentals of machine learning
PART 2 - DEEP LEARNING IN PRACTICE
5.Deep learning for computer vision
6.Deep learning for text and sequences
7.Advanced deep-learning best practices
8.Generative deep learning
9.Conclusions
appendix A - Installing Keras and its dependencies on Ubuntu
appendix B - Running Jupyter notebooks on an EC2 GPU instance
· · · · · · (收起)
讀後感
这本书从6月11号那天老板递到我手里，到今天刚好六周，在这期间我逐字逐句地啃了这本书，并在每周的周二和周五下午给组里的其他人讲这本书，每次讲3个小时。直到五分钟前刚刚讲完最后一章，写了175页的PPT。 感想从何谈起呢？先说Keras吧，这本书的作者是Keras的作者，所以本书...
評分 評分电子版8.4节，从300页开始出现了一个明显的错误，包括代码在内。 原文及代码中 decoder 使用 z = z_mean + exp(z_log_variance) * epsilon 生成 latent space 中的一个点，再依靠这些点的分布生成图像，这实际是对原图像分布的还原过程。 高斯分布可以使用 N~(μ, σ) 来描述，...
評分电子版8.4节，从300页开始出现了一个明显的错误，包括代码在内。 原文及代码中 decoder 使用 z = z_mean + exp(z_log_variance) * epsilon 生成 latent space 中的一个点，再依靠这些点的分布生成图像，这实际是对原图像分布的还原过程。 高斯分布可以使用 N~(μ, σ) 来描述，...
評分目前最通俗易懂的深度学习入门书，由Keras之父执笔。大神不但技术了得，文笔也不一般，真的就是为了让尽可能多的人能够使用深度学习而写的这本书，涵盖了深度学习的基础知识、Keras使用模式以及深度学习最佳实践。 学习本书需要具备基础的Python知识，但不需要深度学习或者机器...
用戶評價
A fantastic book I read these days, not just because the content quality, but also the vision author would like to take us to, the last sentence is remarkable: 1. Staying up to date in a fast-moving field 2. Practice on real-world problems using Kaggle 3. Read about the latest developments on arXiv 4. Explore the Keras ecosystem
评分應該改名deep learning in keras. 不過最後一段對於deep learning的看法和預想倒是很有前瞻性，值得閱讀。
评分菜鳥在此謝過，您的確很淺齣，我去找深入的書瞭
评分應該改名deep learning in keras. 不過最後一段對於deep learning的看法和預想倒是很有前瞻性，值得閱讀。
评分A fantastic book I read these days, not just because the content quality, but also the vision author would like to take us to, the last sentence is remarkable: 1. Staying up to date in a fast-moving field 2. Practice on real-world problems using Kaggle 3. Read about the latest developments on arXiv 4. Explore the Keras ecosystem
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