By Tianjian Sun.
This repository is for code assignments of course INDE577, Data Science and Machine Learning, of Rice University in Fall 2021. In this course, we are learning data science and machine learning algorithms and python-based applications. Course topics consist of supervised learning, unsupervised learning, and optimization methods.
Dr. Randy R. Davila, associate professor of University of Houston-Downtown. Email.
For this repository, each sub-repository is named by an algorithm name, and it contains a .ipynb file which illustrates and impliments algorithms/applications/visualizations learned in that week, a README file, and sub-repositories of dataset/images files (if applicable).
Programming language used in this repository is Python 3.
The following topics have been covered in class:
- Supervised Learning
- K-Nearest Neighbors
- Linear Regression
- Logistic Regression
- Perceptron
- Multilayer Neural Network Using Stochastic/Mini Batch Gradient Descent
- Decision Tree
- Ensemble Learning and Random Forest
- Unsupervised Learning
- Principal Component Analysis and K-Means
- Optimization methods
- Gradient Descent
- Model Comparison