June 2022

Notes for Prof. Hung-Yi Lee's ML Lecture: Normalization
Notes for Prof. Hung-Yi Lee's ML Lecture: Transformer
Notes for Prof. Hung-Yi Lee's ML Lecture: Self-Attention

May 2022

Exception Handling
Thread vs Process
The Curse of Dimensionality
Chap 3: Capital Share Bikeshare Predictor
Chap 3: Capital Share Bikeshare Predictor: Follow the Book

April 2022

Notes for Prof. Hung-Yi Lee's ML Lecture: Reinforcement Learning
Notes for Prof. Hung-Yi Lee's ML Lecture: Ensemble
Notes for Prof. Hung-Yi Lee's ML Lecture: RNN

December 2021

Notes for Prof. Hung-Yi Lee's ML Lecture: Support Vector Machine

October 2021

Notes for Prof. Hung-Yi Lee's ML Lecture: Transfer Learning

September 2021

Notes for Prof. Hung-Yi Lee's ML Lecture: Deep Generative Model
Notes for Prof. Hung-Yi Lee's ML Lecture: More about Auto-Encoder
Notes for Prof. Hung-Yi Lee's ML Lecture 16: Auto-Encoder

August 2021

Notes for Prof. Hung-Yi Lee's ML Lecture 15: Neighbor Embedding
Notes for Prof. Hung-Yi Lee's ML Lecture 14: Word Embedding
Notes for Prof. Hung-Yi Lee's ML Lecture 13: Unsupervised Learning- Linear Methods
Notes for Prof. Hung-Yi Lee's ML Lecture 12: Semi-Supervised Learning
Notes for Prof. Hung-Yi Lee's ML Lecture 11: Why Deep?
Notes for Prof. Hung-Yi Lee's ML Lecture 10: CNN
Notes for Prof. Hung-Yi Lee's ML Lecture 09: Tips for Deep Learning

July 2021

Notes for Prof. Hung-Yi Lee's ML Lecture 7: Backpropagation
Notes for Prof. Hung-Yi Lee's ML Lecture 6: Brief Introduction to Deep Learning
Notes for Prof. Hung-Yi Lee's ML Lecture 5, Classification: Logistic Regression.
Notes for Prof. Hung-Yi Lee's ML Lecture 4, Classification: Probabilistic Generative Model.
Notes for Prof. Hung-Yi Lee's ML Lecture 3, gradient descent.
Notes for Prof. Hung-Yi Lee's ML Lecture 2, Sources of error.
Notes for Prof. Hung-Yi Lee's ML Lecture 1, Regression

June 2021

Notes for Prof. Hung-Yi Lee's ML Lecture 0, Introduction
Sample post