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Description
Some ideas for figures to add to the PPT
- Linear regression, single-layer neural network
- Multilayer Perceptron with hidden layer
- Backpropagation
- Batch Normalization and alternatives
- Computational Graphs
- Dropout
- CNN - padding, stride, pooling,...
- LeNet
- AlexNet
- VGG
- GoogleNet
- ResNet
- DenseNet
- Memory Networks
- RNN
- Deep RNN
- Bidirectional RNN
- GRU
- LSTM
- Language RNN models
- Backpropagation through time
- Encoder-Decoder Architecture
- Seq2seq with RNN encoder-decoder
- Bearm search and other decoding strategies
- Attention
- Multi-head attention
- Self-attention
- Transformer
- Word2vec/GloVe/Skip-gram/CBOW/BERT/GPT....
- Common/Popular CV/NLP Tasks
List adopted from multiple resources including nlpoverview and d2l.ai which both contain a very solid syllabus.
Please feel free to make suggestions below. If you would like to help, also let me know.