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This is the repository for my Advanced Computing courses at the Computer Science and Technology department of Tsinghua University.

License: Creative Commons Attribution 4.0 International

Python 0.89% Jupyter Notebook 12.33% HTML 85.84% C 0.17% TeX 0.54% Java 0.05% C++ 0.12% Shell 0.01% Go 0.04%
tsinghua tsinghua-university thu advanced-computing masters deep-learning machine-learning phd

thu-acp's Introduction

Tsinghua Advanced Computing (2020-26) 🚀

This is the repository for all the courses during my master's and PhD degree in Tsinghua University.

自强不息,厚德载物

Master's

Semester 1

  • Advanced Network Management
  • Chinese Culture and Society
  • Combinatorics and Algorithms design
  • Machine Learning
  • Process and Methods of Software Process Management
  • Upper Intermediate Chinese

Semester 2

  • Deep learning
  • Natural Language Processing

PhD

Semester 1

  • Intermediate Chinese
  • New Horizons in Chinese Philosophy
  • Introduction to Big Data Systems

Semester 2

  • Web Information Retrieval
  • Human Computer Interaction
  • How to Report Research Results in English

Citation

@misc{Sabour2023,
    author       = {Sahand Sabour},
    title        = {{Tsinghua Advanced Computing (2020-26)}},
    year         = 2023,
    publisher    = {Github},
    url          = {https://github.com/Sahandfer/Tsinghua}
    }

Copyright

The contents of this repository is bound by the CC-BY-4.0 license.

thu-acp's People

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thu-acp's Issues

DL HW1

  • Download the dataset
  • Preprocess and plotting
  • Training and Testing

DL HW2

  • Get the dataset and preprocess
  • Softmax for classification
  • MLP for classification
  • Write report
  • Submit to learn

NLP HW2

  • Implement the model
  • Train with/without dropout
  • Train with different hidden size
  • Train with different layer number
  • Train with pre-trained word embedding
  • Write Report
  • Submit
  • Bonus Improve the model

NLP HW1

  • Derive the gradient
  • Preprocess data
  • Implement word2vec
  • Improve word2vec
  • Write report
  • Submit

DL HW5

  • Data pre-processing
  • Get word embedding
  • Implement RNN
  • Write report
  • Submit

DL HW4

  • Implement MLP
  • Implement ConvNet
  • Write report
  • Submit to learn

DL HW3

  • ConvNet for classification
  • Write report
  • Submit to learn

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