Projects

Tutorials #

Machine Learning Tutorials #

Unsupervised Learning
- K-means Clustering
- Principal Component Analysis
- Hierarchical Clustering
Supervised Learning
- Classification:
  - K-Narest Neighbors (KNN)
  - Decision Tree
- Regression
  - Linear Regression
  - Logisitc Regression
- Neural Networks
  - Perceptron
  - Multi-layer Perceptron (MLP) (often referred to as a simple neural network)
  - Convolutional Neural Network (CNN)
  - Recurrent Neural Network (RNN)
  - Long Short-Term Memory (LSTM)
Reinforcement Learning
SVM
- Linear SVM
- Non-linear SVM (using kernels)

Statistics #

Bayesian Statistics
- GitHub Repo
- Website
Event-Based Method

How to Create Online Books #

I gave a talk at YY Lab on how to create onlinebooks.

Website | Code | Slides

Notes on Network Science #

My notes while auditing Professor Yong-Yeol Ahn ’s online course of INFO I606 Network Science

Website | Code | PDF

C101 With Hongtao #

Class website for my students enrolled in MSCH‑C100 Introduction to media at Indiana University Bloomington, 2020 Spring.

“Hongtao was an excellent discussion leader and AI (Associate Instructor). He made the class enjoyable and helped me understand the assignments and was very clear in doing so. His website for our discussion was very helpful and amazing.”

Website | Code

Understanding 3blue1brown’s Videos #

I really like 3blue1brown’s vidoes. I made notes on them:

D3Book Companion #

A simple tutorial website to help beginners like me learn D3.js. It is a side product of my 40 Days of Learning D3 Challenge .

Website | Code | PDF

Data Visualizations #

Modeling & Visualizing American Time Usage Survey (ATUS)

In this project, I modeled ATUS data. I predicted people’s time usage with demographic data as features using neural network (through tensorflow.js). The model performance is very poor but it nonetheless shows how tensorflow.js can be used in this setting.

Demo | Code | Notebook