TODOs

• Activation Function
• Loss Function and Cost Function
• Regularization
• Optimizer
• Backpropagation
• Dropout

• Bachnormalization
• Data Preprocessing
• checklist for basic things to get right to make you NN work

https://arxiv.org/pdf/1511.05952.pdf

• Archimedes' constant π
• Euler's number e.
• Pythagoras' constant √2.
• The imaginary unit i.
• The Feigenbaum constants α and δ
• Apéry's constant ζ(3)
• The golden ratio φ
• The Euler–Mascheroni constant γ
• Binomial Theorm

https://medium.com/emergent-future/simple-reinforcement-learning-with-tensorflow-part-0-q-learning-with-tables-and-neural-networks-d195264329d0#.lb3816462

http://people.eecs.berkeley.edu/~pabbeel/nips-tutorial-policy-optimization-Schulman-Abbeel.pdf

https://github.com/karpathy/paper-notes

https://github.com/terryum/awesome-deep-learning-papers#understanding--generalization--transfer

• Monte Carlo Methods
• Temporal-Difference Learning
• Multi-step Bootstrapping
• Planning and Learning with Tabular Methods
• On-policy Prediction with Approximation
• On-policy Control with Approximation
• On-policy Methods with Approximation
• Eligibility Traces
• Policy Gradient Methods