Notebooks for a 1-day crash course. It aims for teaching deep learning in a single day. This repo contains the notebooks with only simplified code blocks. The texts are also summarized into slides that will be uploaded later.
Check the wiki page for instructions to setup the running environments.
| title | ipynb | slides |
|---|---|---|
| Data Manipulation with Ndarray | github | nbviewer |
| Automatic Differentiation | github | nbviewer |
| Linear Regression Implementation from Scratch | github | nbviewer |
| Concise Implementation of Linear Regression | github | nbviewer |
| Image Classification Data (Fashion-MNIST) | github | nbviewer |
| Implementation of Softmax Regression from Scratch | github | nbviewer |
| Concise Implementation of Softmax Regression | github | nbviewer |
| Implementation of Multilayer Perceptron from Scratch | github | nbviewer |
| Concise Implementation of Multilayer Perceptron | github | nbviewer |
| title | ipynb | slides |
|---|---|---|
| GPUs | github | nbviewer |
| Convolutions | github | nbviewer |
| Pooling | github | nbviewer |
| Convolutional Neural Networks (LeNet) | github | nbviewer |
| Deep Convolutional Neural Networks (AlexNet) | github | nbviewer |
| Networks Using Blocks (VGG) | github | nbviewer |
| Inception Networks (GoogLeNet) | github | nbviewer |
| Residual Networks (ResNet) | github | nbviewer |
| title | ipynb | slides |
|---|---|---|
| A Hybrid of Imperative and Symbolic Programming | github | nbviewer |
| Multi-GPU Computation Implementation from Scratch | github | nbviewer |
| Concise Implementation of Multi-GPU Computation | github | nbviewer |
| Fine Tuning | github | nbviewer |
| title | ipynb | slides |
|---|---|---|
| Text Preprocessing | github | nbviewer |
| Implementation of Recurrent Neural Networks from Scratch | github | nbviewer |
| Concise Implementation of Recurrent Neural Networks | github | nbviewer |
| Gated Recurrent Units (GRU) | github | nbviewer |
| Long Short Term Memory (LSTM) | github | nbviewer |