This is a brief summary of ML course provided by Andrew Ng and Stanford in Coursera.
You can find the lecture video and additional materials in
https://www.coursera.org/learn/machine-learning/home/welcome
Theories and exercises will be used in this coursework.
In this class, you can learn about the state of the are and also gain practice implementing and deploying these algorithms.
- Web Search Engine: Learning algorithm has learned how to rank web pages.
- SNS: Friends recognition
- Spam Filters
Learning Algorithms mimic how human brain learns.
Why ML so Prevalent today?
- Grew out of work in AI
- To build intelligent machines, machine had to learning it by itself as a new capability for computers.
Examples:
- DB Mining: large datasets from growth of automation/ web. e.g., Web click data, Medical records, Biology, Engineering
- Applications can't program by hand e.g., Autonomous helicopter, Handwriting recognition, most of NLP, Computer vision
- Self-customizing programs e.g., Amazon, Netflix product recommendations
- Understanding human learning (brain, real AI)
