…by Hagan Demuth and Kneale, (q) Neural Networks, A Comprehensive Foundation (2nd edition) - By Haykin (there is a newer edition out but I don't know anything about that, this is the one I used) (r) Neural Networks for Pattern Recognition ( Bishop). At this point you are in good shape to read any papers in NN. My reccomendations - anything by Yann LeCun and Geoffrey Hinton. Both do amazing research. Reinforcement Learning (s) Reinforcement…
……适合初学者。1. Gilbert Strang 的《Linear Algebra》 2. Gilbert Strang 的《Calculus》 3. Russell 和 Norvig 的《Artificial Intelligence A Modern Approach》 4. Tom Mitchell 的《Machine Learning》 5. Chris Bishop 的《Neural Networks for Pattern Recognition》 6. Peter Norvig 的《Paradigms of Artificial Intelligence Programming》（好吧，这本不算前沿的 AI 书，但在我看来这是有史以来写得最好的一本编程书，而且……
…for beginners. 1. Linear Algebra by Gilbert Strang 2. Calculus by Gilbert Strang 3. Artificial Intelligence A Modern Approach By Russell and Norvig 4. Machine Learning By Tom Mitchell 5. Neural Networks for Pattern Recognition by Chris Bishop 6. Paradigms of Artificial Intelligence Programming by Peter Norvig (ok, this one is not quite an cutting edge AI book, but imo this is the best book on programming ever written and…
我赞同关于第 2 点的看法。我有 Russell 和 Norvig 的那本，也觉得是本好书，但我不确定这两者究竟有多少重叠。我也没有 PRML，不过 Bishop 的《Neural Networks for Pattern Recognition》非常出色（而且包含了很多非 NN 相关的内容）。ESL 棒极了，在我看来是现代机器学习领域最好的教材。它涵盖了 PCI 里的许多主题，而且深度都很合理……
I agree about #2. I have Russell and Norvig and agree that it is an excellent book, but I am not sure how much overlap there truly is here. I also do not have PRML, but Neural Networks for Pattern Recognition by Bishop is excellent (and includes many non-NN related items). ESL is excellent and, to me, the best modern text in machine learning. It covers many of the topics in PCI both at a reasonable level…
……关于神经网络的推荐如下：- 并行分布式处理（PDP 组第 1 & 2 卷）- Simon Haykin（《Neural Networks and Learning Machines》）- Christopher Bishop（《Neural Networks for Pattern Recognition》）
…recommendations (for neural networks) would be as follows: - parallel distributed processing (PDP group vol 1 & 2) - simon haykin (Neural Networks and Learning Machines) - christopher bishop (Neural Networks for Pattern Recognition)
……与神经网络（的大多数用法）截然不同的视角，后者在模型本身和如何对其进行推理之间并没有如此清晰的划分。搞笑的是，Chris Bishop 在 1995 年写了教材《Neural Networks for Pattern Recognition》，而现在实际上却在反对使用神经网络。你可以两者兼用，把神经网络作为概率模型里的“因子（factors）”（那些黑色方块）。
…different perspective from (most uses of) neural networks, which do not have this clear separation between the model and how to reason about it. It's funny that Chris Bishop in 1995 wrote the textbook "Neural Networks for Pattern Recognition" and now is effectively arguing against using neural networks. You can use both by using neural networks as "factors" (the black squares) in probabilistic models.
他对 Black 的《Neural Networks for Pattern Recognition》的书评让我乐了，而且非常符合我自己读这本书的体会。那位评论者说“我本来指望在这本书里对神经网络有个深入的了解。结果，几乎每一个……
His review of Black's 'Neural Networks for Pattern Recognition' made me chuckle, and accorded with my own experience of the book. To the reviewer who said "I was looking forward to a detailed insight into neural networks in this book. Instead, almost every…
……作者是 Hagan、Demuth 和 Beale，(q)《Neural Networks, A Comprehensive Foundation》（第 2 版）——Haykin 著（出了更新的版本，但我不了解，我用的是这版）(r)《Neural Networks for Pattern Recognition》（Bishop 著）。学到这里，你读任何 NN（神经网络）论文都毫无压力了。我的建议是——Yann LeCun 和 Geoffrey Hinton 的任何论文都行。两位做的研究都太神了。强化学习（Reinforcement Learning）(s) Reinforcement……
…by Hagan Demuth and Kneale, (q) Neural Networks, A Comprehensive Foundation (2nd edition) - By Haykin (there is a newer edition out but I don't know anything about that, this is the one I used) (r) Neural Networks for Pattern Recognition ( Bishop). At this point you are in good shape to read any papers in NN. My reccomendations - anything by Yann LeCun and Geoffrey Hinton. Both do amazing research. Reinforcement Learning (s) Reinforcement…
……适合初学者。1. Gilbert Strang 的《Linear Algebra》 2. Gilbert Strang 的《Calculus》 3. Russell 和 Norvig 的《Artificial Intelligence A Modern Approach》 4. Tom Mitchell 的《Machine Learning》 5. Chris Bishop 的《Neural Networks for Pattern Recognition》 6. Peter Norvig 的《Paradigms of Artificial Intelligence Programming》（好吧，这本不算前沿的 AI 书，但在我看来这是有史以来写得最好的一本编程书，而且……
…for beginners. 1. Linear Algebra by Gilbert Strang 2. Calculus by Gilbert Strang 3. Artificial Intelligence A Modern Approach By Russell and Norvig 4. Machine Learning By Tom Mitchell 5. Neural Networks for Pattern Recognition by Chris Bishop 6. Paradigms of Artificial Intelligence Programming by Peter Norvig (ok, this one is not quite an cutting edge AI book, but imo this is the best book on programming ever written and…
我赞同关于第 2 点的看法。我有 Russell 和 Norvig 的那本，也觉得是本好书，但我不确定这两者究竟有多少重叠。我也没有 PRML，不过 Bishop 的《Neural Networks for Pattern Recognition》非常出色（而且包含了很多非 NN 相关的内容）。ESL 棒极了，在我看来是现代机器学习领域最好的教材。它涵盖了 PCI 里的许多主题，而且深度都很合理……
I agree about #2. I have Russell and Norvig and agree that it is an excellent book, but I am not sure how much overlap there truly is here. I also do not have PRML, but Neural Networks for Pattern Recognition by Bishop is excellent (and includes many non-NN related items). ESL is excellent and, to me, the best modern text in machine learning. It covers many of the topics in PCI both at a reasonable level…
……关于神经网络的推荐如下：- 并行分布式处理（PDP 组第 1 & 2 卷）- Simon Haykin（《Neural Networks and Learning Machines》）- Christopher Bishop（《Neural Networks for Pattern Recognition》）
…recommendations (for neural networks) would be as follows: - parallel distributed processing (PDP group vol 1 & 2) - simon haykin (Neural Networks and Learning Machines) - christopher bishop (Neural Networks for Pattern Recognition)
……与神经网络（的大多数用法）截然不同的视角，后者在模型本身和如何对其进行推理之间并没有如此清晰的划分。搞笑的是，Chris Bishop 在 1995 年写了教材《Neural Networks for Pattern Recognition》，而现在实际上却在反对使用神经网络。你可以两者兼用，把神经网络作为概率模型里的“因子（factors）”（那些黑色方块）。
…different perspective from (most uses of) neural networks, which do not have this clear separation between the model and how to reason about it. It's funny that Chris Bishop in 1995 wrote the textbook "Neural Networks for Pattern Recognition" and now is effectively arguing against using neural networks. You can use both by using neural networks as "factors" (the black squares) in probabilistic models.
他对 Black 的《Neural Networks for Pattern Recognition》的书评让我乐了，而且非常符合我自己读这本书的体会。那位评论者说“我本来指望在这本书里对神经网络有个深入的了解。结果，几乎每一个……
His review of Black's 'Neural Networks for Pattern Recognition' made me chuckle, and accorded with my own experience of the book. To the reviewer who said "I was looking forward to a detailed insight into neural networks in this book. Instead, almost every…