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*** [https://sites.ualberta.ca/~szepesva/RLBook.html Csaba Szepesvári. Algorithms for Reinforcement Learning] | *** [https://sites.ualberta.ca/~szepesva/RLBook.html Csaba Szepesvári. Algorithms for Reinforcement Learning] | ||
*** [http://dl.acm.org/citation.cfm?id=2670001 Marco Wiering and Martijn van Otterlo. Reinforcement Learning: State-of-the-Art] | *** [http://dl.acm.org/citation.cfm?id=2670001 Marco Wiering and Martijn van Otterlo. Reinforcement Learning: State-of-the-Art] | ||
+ | ** [http://www.kdnuggets.com/2017/04/10-free-must-read-books-machine-learning-data-science.html KDNuggets "10 Free Must-Read Books for Machine Learning and Data Science"] | ||
* Online resources: | * Online resources: | ||
** [https://www.coursera.org/learn/machine-learning Andrew Ng's free online Coursera Machine Learning course] | ** [https://www.coursera.org/learn/machine-learning Andrew Ng's free online Coursera Machine Learning course] | ||
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** [http://www.cs.waikato.ac.nz/ml/weka/ Weka Java-based Data Mining software] and [http://dl.acm.org/citation.cfm?id=1205860 Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques] | ** [http://www.cs.waikato.ac.nz/ml/weka/ Weka Java-based Data Mining software] and [http://dl.acm.org/citation.cfm?id=1205860 Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques] | ||
** [http://modelai.gettysburg.edu/ Model AI Assignments] | ** [http://modelai.gettysburg.edu/ Model AI Assignments] | ||
+ | ** [https://ml.berkeley.edu/blog/tutorials/ Berkeley student crash course on ML] | ||
* Recommendations: | * Recommendations: | ||
** [https://www.quora.com/How-do-I-learn-machine-learning-1 Quora "How do I learn machine learning?" answers] | ** [https://www.quora.com/How-do-I-learn-machine-learning-1 Quora "How do I learn machine learning?" answers] | ||
** [https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md Joseph Misiti's Machine Learning book recommendations] | ** [https://github.com/josephmisiti/awesome-machine-learning/blob/master/books.md Joseph Misiti's Machine Learning book recommendations] | ||
+ | ==Neural Network Learning== | ||
+ | *Textbooks | ||
+ | ** [http://www.deeplearningbook.org/ Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville] | ||
+ | ** [http://neuralnetworksanddeeplearning.com/ Michael Nielson's Neural Networks and Deep Learning online book.] | ||
+ | *Websites | ||
+ | ** [https://www.facebook.com/groups/DeepNetGroup/ Waikit Lau and Arthur Chan's Artificial Intelligence and Deep Learning (AIDL) Facebook group] and [https://www.facebook.com/groups/DeepNetGroup/permalink/385843868475168/ FAQ] | ||
+ | ** [http://yerevann.com/a-guide-to-deep-learning/ A Guide to Deep Learning by YerevaNN Labs] | ||
+ | ** [http://p.migdal.pl/2017/04/30/teaching-deep-learning.html Piotr Migdał's Learning Deep Learning with Keras] | ||
+ | ** [http://aiplaybook.a16z.com/docs/reference/links a16z team's reference links] | ||
+ | ** [http://cs231n.github.io/convolutional-networks/ Stanford's CS 231n Convolutional Networks course website] | ||
+ | ** various Wikipedia pages concerning [https://en.wikipedia.org/wiki/Artificial_neural_network artificial neural networks] | ||
+ | ** [http://playground.tensorflow.org/ TensorFlow Playground] | ||
+ | ** [https://distill.pub/2017/momentum/ Why Momentum Really Works] | ||
+ | ** [http://lamda.nju.edu.cn/weixs/project/CNNTricks/CNNTricks.html Xiu-Shen Wei's Must Know Tips/Tricks in Deep Neural Networks] | ||
+ | ** [https://medium.com/towards-data-science/secret-sauce-behind-the-beauty-of-deep-learning-beginners-guide-to-activation-functions-a8e23a57d046 Medium.com guide: Understanding Activation Functions] | ||
+ | ** [https://github.com/williamFalcon/DeepRLHacks John Schulman's Deep RL Hacks (summarized by William Falcon)] | ||
+ | *Online Courses | ||
+ | ** [https://www.coursera.org/learn/machine-learning Andrew Ng's Machine Learning course] and [https://www.coursera.org/specializations/deep-learning Coursera Deep Learning specialization] | ||
+ | ** [https://www.coursera.org/learn/neural-networks Geoffrey Hinton's Neural Networks for Machine Learning course] | ||
+ | ** [http://www.dmi.usherb.ca/~larocheh/neural_networks Hugo Larochelle's graduate-level online Neural Network course] | ||
+ | ** [https://medium.freecodecamp.org/dive-into-deep-learning-with-these-23-online-courses-bf247d289cc0 David Venturi's list of Deep Learning online courses] | ||
+ | ** [http://thegrandjanitor.com/2016/08/15/learning-deep-learning-my-top-five-resource/ Arthur Chan's top 5] | ||
+ | *Software | ||
+ | ** [https://www.tensorflow.org/ TensorFlow] and [https://keras.io/ Keras] | ||
+ | ** [https://github.com/Microsoft/cntk Microsoft Cognitive Toolkit (CNTK)] | ||
+ | ** [https://github.com/Theano/Theano Theano] | ||
+ | ** [http://torch.ch/ Torch] and [http://pytorch.org/ PyTorch]) | ||
+ | ** [http://caffe.berkeleyvision.org/ Caffe] | ||
+ | ** [http://mxnet.io/ MXNet] | ||
+ | ** [https://deeplearning4j.org/ DeepLearning4J] | ||
+ | ** [https://en.wikipedia.org/wiki/Comparison_of_deep_learning_software Comparison of deep learning software] and [https://twitter.com/fchollet/status/852194634470223873 April 2017 popularity metrics] | ||
+ | *Hardware | ||
+ | ** [http://timdettmers.com/2017/04/09/which-gpu-for-deep-learning Tim Dettmers' GPU comparison study] | ||
+ | ** [https://d4datascience.wordpress.com/2017/05/06/setting-up-a-gpu-based-deep-learning-machine/ Ved's d4datascience blog entry on setting up a GPU-based deep learning machine] |
Revision as of 11:45, 13 September 2017
Starting Places
General
Machine Learning
- Texts:
- Christopher Bishop. Pattern Recognition and Machine Learning
- Kevin Murphy. Machine Learning: A Probabilistic Perspective
- David Barber. Probabilistic Reasoning and Machine Learning (Barber's free PDF version)
- Tom Mitchell. Machine Learning
- Ethem Alpaydin. Introduction to Machine Learning
- Statistical Learning:
- Reinforcement Learning:
- KDNuggets "10 Free Must-Read Books for Machine Learning and Data Science"
- Online resources:
- Andrew Ng's free online Coursera Machine Learning course
- UC Irvine Machine Learning Repository
- Kaggle datasets
- RStudio software for labs
- Weka Java-based Data Mining software and Ian Witten and Eibe Frank. Data Mining: Practical Machine Learning Tools and Techniques
- Model AI Assignments
- Berkeley student crash course on ML
- Recommendations:
Neural Network Learning
- Textbooks
- Websites
- Waikit Lau and Arthur Chan's Artificial Intelligence and Deep Learning (AIDL) Facebook group and FAQ
- A Guide to Deep Learning by YerevaNN Labs
- Piotr Migdał's Learning Deep Learning with Keras
- a16z team's reference links
- Stanford's CS 231n Convolutional Networks course website
- various Wikipedia pages concerning artificial neural networks
- TensorFlow Playground
- Why Momentum Really Works
- Xiu-Shen Wei's Must Know Tips/Tricks in Deep Neural Networks
- Medium.com guide: Understanding Activation Functions
- John Schulman's Deep RL Hacks (summarized by William Falcon)
- Online Courses
- Software
- Hardware