我真的很喜欢 Aggarwal 的《Neural Networks and Deep Learning》。强烈推荐。（至少今年夏天 Springer 在免费送 PDF——不确定现在还有没有。）在我看来，Goodfellow 等人在前一百五十页讲的内容虽然重要，……
I really like Aggarwal's "Neural Networks and Deep Learning". I recommend it highly. (At least this summer Springer was giving away a PDF - not sure if that's still true.) To me, Goodfellow et al. spent the first hundred and fifty pages on stuff which is important,…
……重于实现，所以它更适合用来对机器学习的基础建立有章可循的系统理解，而不是让你快速上手解决实际问题所需的现代工具。2. 《Neural Networks and Deep Learning》- Nielson 这是一本免费的在线书，通俗易懂且引人入胜。它涵盖了基础理论，并用 Python 实现了示例。
…over implementation so it's more for developing a principled understanding of machine learning fundamentals than for getting you up to speed with modern tools necessary for solving real problems. 2. "Neural Networks and Deep Learning" - Nielson This is a free online book that is very accessible and engaging. It covers basic theory and implements examples in Python.
From the yc reading list 2015 [http://themacro.com/articles/2015/12/yc-2015-reading-list/], they recommend [for Neural Networks] this book: http://neuralnetworksanddeeplearning.com/
It's more about understanding than "learning tools."
Looking at headers:
Last-Modified: Tue, 30 Apr 1996 18:53:31 GMT
Still, looks good, if a bit dated. For me, these two tutorials were the ones that helped me understand NN the most:
- http://neuralnetworksanddeeplearning.com/
- https://mattmazur.com/2015/03/17/a-step-by-step-backpropagat...
……与归纳逻辑 - John Kruschke - 《Doing Bayesian Data Analysis》 - Gareth Williams - 《Linear Algebra with Applications, Alternate Edition》 - Matthew Scarpino - 《OpenCL in Action》 - Michael Nielsen - 《Neural Networks and Deep Learning》 - Goodfellow、Bengio 和 Courville - 《Deep Learning》
…and Inductive Logic - John Kruschke - Doing Bayesian Data Analysis - Gareth Williams - Linear Algebra with Applications, Alternate Edition - Matthew Scarpino - OpenCL in Action - Michael Nielsen - Neural Networks and Deep Learning - Goodfellow, Bengio, and Courville - Deep Learning
For anyone looking for a broad intro to neural networks, I read a bunch of stuff when I was getting started and these two were the most outstanding:
http://neuralnetworksanddeeplearning.com/
http://cs231n.stanford.edu/
我真的很喜欢 Aggarwal 的《Neural Networks and Deep Learning》。强烈推荐。（至少今年夏天 Springer 在免费送 PDF——不确定现在还有没有。）在我看来，Goodfellow 等人在前一百五十页讲的内容虽然重要，……
I really like Aggarwal's "Neural Networks and Deep Learning". I recommend it highly. (At least this summer Springer was giving away a PDF - not sure if that's still true.) To me, Goodfellow et al. spent the first hundred and fifty pages on stuff which is important,…
……重于实现，所以它更适合用来对机器学习的基础建立有章可循的系统理解，而不是让你快速上手解决实际问题所需的现代工具。2. 《Neural Networks and Deep Learning》- Nielson 这是一本免费的在线书，通俗易懂且引人入胜。它涵盖了基础理论，并用 Python 实现了示例。
…over implementation so it's more for developing a principled understanding of machine learning fundamentals than for getting you up to speed with modern tools necessary for solving real problems. 2. "Neural Networks and Deep Learning" - Nielson This is a free online book that is very accessible and engaging. It covers basic theory and implements examples in Python.
出自 2015 年 YC 阅读清单 [http://themacro.com/articles/2015/12/yc-2015-reading-list/]，他们推荐[针对神经网络]这本书：http://neuralnetworksanddeeplearning.com/ 它更侧重于理解，而非“学习工具”。
From the yc reading list 2015 [http://themacro.com/articles/2015/12/yc-2015-reading-list/], they recommend [for Neural Networks] this book: http://neuralnetworksanddeeplearning.com/ It's more about understanding than "learning tools."
看响应头： Last-Modified: Tue, 30 Apr 1996 18:53:31 GMT 不过看起来还不错，虽然有点过时。对我来说，这两个教程是帮我理解神经网络最多的： - http://neuralnetworksanddeeplearning.com/ - https://mattmazur.com/2015/03/17/a-step-by-step-backpropagat...
Looking at headers: Last-Modified: Tue, 30 Apr 1996 18:53:31 GMT Still, looks good, if a bit dated. For me, these two tutorials were the ones that helped me understand NN the most: - http://neuralnetworksanddeeplearning.com/ - https://mattmazur.com/2015/03/17/a-step-by-step-backpropagat...
……与归纳逻辑 - John Kruschke - 《Doing Bayesian Data Analysis》 - Gareth Williams - 《Linear Algebra with Applications, Alternate Edition》 - Matthew Scarpino - 《OpenCL in Action》 - Michael Nielsen - 《Neural Networks and Deep Learning》 - Goodfellow、Bengio 和 Courville - 《Deep Learning》
…and Inductive Logic - John Kruschke - Doing Bayesian Data Analysis - Gareth Williams - Linear Algebra with Applications, Alternate Edition - Matthew Scarpino - OpenCL in Action - Michael Nielsen - Neural Networks and Deep Learning - Goodfellow, Bengio, and Courville - Deep Learning
对于任何想广泛入门神经网络的人，我刚开始时读了很多材料，其中这两个最出色： http://neuralnetworksanddeeplearning.com/ http://cs231n.stanford.edu/
For anyone looking for a broad intro to neural networks, I read a bunch of stuff when I was getting started and these two were the most outstanding: http://neuralnetworksanddeeplearning.com/ http://cs231n.stanford.edu/