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Please leave your comments: Blog issues or Demo issues

Issues include but not limited to:

• Potential topics: any interesting topic which has not been contained.
• Suggestions on coding.
• Share your perspectives
• Raise issues.
• ...
• ...

• Demo: Gaussian Process Demo
• Understanding: Gaussian Process 高斯过程

• Demo: K-mean Demo
• Understanding: K-means and Latent variable model

• Demo
• Understanding:

• Demo: CRF
• Understanding:

• Demo: GBDT
• Understanding: TBD

• Linear Regression
• Logisctic Regression
• Support Vector Machine (SVM)
• Principal Components Analysis (PCA)
• Decision Tree and Random Forest (Bagging)
• Adaboost, Xgboost (Boosting)

• PyTorch Demo: Transformer
• Paper: Attention Is All You Need
• Application: Sequence tagging task; Topic classfication; Chatbot and other text generation tasks.

• PyTorch Demo: BERT
• Paper: BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
• Application: NER and other sequence tagging task, Topic classfication.

• Pytorch Demo: VAE
• Paper: Auto-Encoding Variational Bayes
• Understanding: Variational AutoEncoder
• Application: Natural Language Generation

• Pytorch Demo: PointNet
• Paper: Pointer Networks
• Understanding: TBD
• Application: Coreference, Rewrite sentence.

• Demo with Description: Word_segmentation

• Data preparation
• NER with LSTM
• NER with pretrained BERT

• Data preparation: additional process needed
• NLU with Transformer
• NLU with pretrained BERT

• Data
• NLG using VAE

• Data
• Seq2Seq ChatBot with LSTM

• Bootstrap
• SnowBall

Wanna deploying your Pytroch model? Please try to build a simple Flask serving:

• Flask Demo: Flask Demo NLU
• Tutorials:
  • Pytorch 模型部署I--Torch2ONNX
  • Pytorch/ONNX 模型部署II -- Using Flask
• Official webs: Deplying Pytorch in Python via flask