Note for Coursera : Supervised Machine Learning: Regression and Classification
1. To implement the model 𝑓𝑤,𝑏 for linear regression with one variable
linear regression
Decision Tree Implementations
This is an exercise from Intro to ML with Tensor Flow – Scholarship Program Nanodegree Program
Calculating Information Gain of Different Split Criteria:
Style Transfer & DeepTraffic
Canny Edge Detection
Fourier Transform of Filters
HSV MASK & RGB MASK
Fourier Transform
Lesson 2: Introduction to Neural Networks_II
Udacity: Intro to Deep Learning with PyTorch:
– Logistic Regression:
- Take your data
- Pick a random model
- Calculate the error
- Minimize the error, and obtain a better model
– Calculating the Error Function
Lesson 2: Introduction to Neural Networks_I
Udacity: Intro to Deep Learning with PyTorch:
Lesson 2: Introduction to Neural Networks
– Why “Neural Networks”?
Gina Hsu 