├── .gitignore ├── CS229 ├── EM.ipynb ├── GLM.ipynb ├── RL1.ipynb └── RL2.ipynb ├── Deep-Learning ├── back-propagation-in-matrix-form.ipynb ├── back-propagation-through-time.ipynb ├── install-caffe-in-windows.ipynb ├── keras-notes │ └── keras-tips.ipynb ├── mxnet-notes │ ├── 1-installation.ipynb │ ├── 2-mxnet-symbolic.ipynb │ ├── mshadow-expression-template-tutorial.ipynb │ ├── mshadow-note2-data-structures.ipynb │ └── operators-in-mxnet.ipynb ├── rnn-numpy.ipynb ├── singular-value-of-random-matrix.ipynb └── theano-notes │ ├── part2-simple-computations.ipynb │ ├── part3-shared-variable.ipynb │ ├── part4-random-number.ipynb │ ├── part6-scan-function.ipynb │ └── part7-dimshuffle.ipynb ├── ML-Foundation └── lecture-1.ipynb ├── Machine-Learning ├── implement-softmax-in-theano.ipynb ├── softmax-crossentropy-derivative.ipynb ├── svd-ridge-regression.ipynb ├── svd1.ipynb └── xgboost-notes │ └── xgboost-note1.ipynb ├── Math └── Convex Optimization │ └── 2-convex-set.ipynb ├── NLP ├── 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