Machine Learning Course
An 11-WEEK course (55-hour) provided by Stanford University on Coursera and explained by Andrew Ng. The course gives a broad introduction to machine learning, data-mining, and statistical pattern recognition.
Topics Covered
- Supervised learning
- Parametric/non-parametric algorithms
- Support vector machines
- Kernels
- Neural Networks
- Unsupervised learning
- Dimensionality reduction
- Recommender systems
- Deep learning
- Best practices in machine learning
- Bias/variance theory
- Innovation process in machine learning and AI
Repo Contents
- Lectures of the instructor
- Programming Assignments
- My brief notes during the course
Most of notes in notes document are copied from the lectures, my own notes are added as comment lines between /* */ so they may contain incorrect info
Certificate
Reference
Stanford University - Andrew Ng - Machine Learning Course