leocecilia/ml2017fall

Works for Machine Learning (2017 FALL) @ NTU

ML2017FALL

The repository is made to keep my works for the course: Machine Learning (2017 Fall), held by Prof. Hung-Yi Lee, National Taiwan University.

Course Description

Learning the basic theory of machine learning and various applications.

Course map

Contents

• hw0: Python prerequisite testing
• hw1: PM2.5 Prediction using (linear) regression with gradient descent optimization.
• hw2: Income (Binary) Classification using logistic regression and other machine learning approaches.
• hw3: Image Sentiment Classification using convolutional neural networks.
• hw4: Text Sentiment Classification using word embedding and recurrent neural networks.
• hw5: Movie Recommendation using matrix factorization.
• hw6: Dimension Reduction and Clustering using PCA and KMeans clustering.

Environment

Python 3.5.3 tensorflow 1.3.0 Keras 2.0.8 scikit-learn 0.19.0 and others