- python http://docs.python-guide.org/en/latest/intro/learning/
- Jupyter http://jupyter-notebook-beginner-guide.readthedocs.io/en/latest/
- Scipy http://www.scipy-lectures.org/
- Pandas https://pandas.pydata.org/pandas-docs/stable/10min.html
- Scikit-Learn http://scikit-learn.org/stable/user_guide.html
- Seaborn charts https://seaborn.pydata.org/tutorial.html
- brief intro to Neural nets https://www.toptal.com/machine-learning/an-introduction-to-deep-learning-from-perceptrons-to-deep-networks
- Spark MLLib https://spark.apache.org/mllib/
- Mathematical Foundations of Machine Learning: https://www.youtube.com/playlist?list=PLD0F06AA0D2E8FFBA
- neural networks refresher - https://www.youtube.com/playlist?list=PLiaHhY2iBX9hdHaRr6b7XevZtgZRa1PoU
- DL tutorial - theano code, briefly covers all topics http://deeplearning.net/tutorial/
- Learning TensorFlow https://learningtensorflow.com/
- Jason Brownlee's blog - all Keras / LTSM tutorials http://machinelearningmastery.com/blog/
- TensorFlow docs https://www.tensorflow.org/api_docs/python/
- Keras docs - https://keras.io/
- Google Cloud Machine Learning - TensorFlow scale out https://cloud.google.com/ml-engine/docs/
- TensorFlow Cookbook https://github.com/nfmcclure/tensorflow_cookbook
- deep learning textbook online http://www.deeplearningbook.org/
- a study guide: http://yerevann.com/a-guide-to-deep-learning/
- beyond Deep Learning - Reinforcement Learning: blog series: https://github.com/dennybritz/reinforcement-learning
- summary of bleeding edge: OpenAI blogs: https://blog.openai.com/