/ML2017FALL

Machine Learning (EE 5184) in NTU

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ML2017FALL

Lecturer: Prof. Hung-yi Lee
Course website: http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML17_2.html

Repo. content

  1. Predict PM2.5 using linear regression. [link] [kaggle]. Top28%

  2. Predict income using logistic regression and gradient boosting tree. [link] [kaggle]. Top1%

  3. Image sentiment classification using convolutional neural network (CNN). [link] [kaggle]. Top2%

  4. Text sentiment classification using recurrent neural network (LSTM) [link] [kaggle]. Top1%

  5. Predict movie ratings using Matrix factorization [link] [kaggle]. Top1%

  6. Image clustering (unsupervised learning) [link] [kaggle]. Top2%

[Final] Listen and Translate (ASR+translation) [link] [Kaggle].Top6%