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# Papers
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 - [Models for Understanding versus Models for Prediction](papers/RC1581.pdf) 
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 - [End to End Learning for Self-Driving Cars](https://devblogs.nvidia.com/parallelforall/deep-learning-self-driving-cars/)
 - [Can we open the black box of AI?](http://www.nature.com/news/can-we-open-the-black-box-of-ai-1.20731)
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 - [Group Behavior from Video: A Data-Driven Approach to Crowd Simulation](http://mrl.snu.ac.kr/research/ProjectVideoCrowd/Group_Behavior_SCA2007.pdf)
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 - [LSTM Human Trajectory Prediction in Crowd](https://gitlab.version.fz-juelich.de/chraibi1/Machine_Learning/blob/master/papers/Social_LSTM_Human_Trajectory_Prediction_in_Cr.pdf)
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# Books
 - [Reinforcement Learning: An Introduction (PDF)](https://webdocs.cs.ualberta.ca/~sutton/book/bookdraft2016sep.pdf)
 - [Understanding Machine Learning: From Theory to Algorithms (PDF)](http://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf)
 - [Introduction to Machine Learning (PDF)](http://ai.stanford.edu/~nilsson/MLBOOK.pdf)
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# Links 
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 - [Yann LeCun’s Keynote on Predictive Learning](https://iot-for-all.com/yann-lecuns-keynote-on-predictive-learning-mixed-reality-as-imagined-by-magic-leap-and-marc-f2adfecf7ab6#.ia8jwksvl)
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 - [The AI Programmer's Bookshelf](http://alumni.media.mit.edu/~jorkin/aibooks.html)
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 - [How to Get Started with machine learning](https://news.ycombinator.com/item?id=12713056) 
 - [Introduction to Machine Learning for Developers](http://blog.algorithmia.com/introduction-machine-learning-developers/)
 - [machine-learning-way-easier-than-it-looks](https://blog.intercom.com/machine-learning-way-easier-than-it-looks/)
 - [Big Data’s Mathematical Mysteries](https://www.quantamagazine.org/20151203-big-datas-mathematical-mysteries/)
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 - [A course in machine learning](http://ciml.info/)
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 - [machine-learning-for-everyday-tasks](http://blog.mailgun.com/machine-learning-for-everyday-tasks/)
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 - [What's Wrong With Deep Learning?](http://www.pamitc.org/cvpr15/files/lecun-20150610-cvpr-keynote.pdf)
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# Videos 
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 - [Autonomous driving](https://www.coursera.org/learn/machine-learning/lecture/zYS8T/autonomous-driving)
 - [R vs PYTHON](https://blog.dominodatalab.com/video-huge-debate-r-vs-python-data-science/)
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# Code 
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- [TensorFlow](https://www.tensorflow.org/)
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- [deepmind/learning-to-learn](https://github.com/deepmind/learning-to-learn)