Machine Learning — Coursera
This course ranks first in the top best online Machine Learning courses. This is a course where all other machine learning courses are reviewed. This beginner's course is a professor at Stanford University, a co-founder of Google Brain, a co-founder of Coursera, and a vice president who has grown Baidu's AI team to include thousands of scientists. It was taught and created by one Andrew Ng.
This course uses the open source Octave programming language instead of Python or R. This may not be a big deal for some, but if you're a complete beginner, Octave is an easy way to learn the basics of ML. Overall, the course material is very rounded and intuitively represented by Ng. The mathematics needed to understand each algorithm is fully explained, with some explanations about calculus and a review of linear algebra. This course is fairly self-contained, but any prior knowledge of linear algebra will help.
Course structure:
- Linear Regression with One Variable
- Linear Algebra Review
- Linear Regression with Multiple Variables
- Octave/Matlab Tutorial
- Logistic Regression
- Regularization
- Neural Networks: Representation
- Neural Networks: Learning
- Advice for Applying Machine Learning
- Machine Learning System Design
- Support Vector Machines
- Dimensionality Reduction
- Anomaly Detection
- Recommender Systems
- Large Scale Machine Learning
- Application Example: Photo OCR
All of this will be covered in 11 weeks. If you promise to complete the entire course, you will have a good understanding of machine learning in about four months. Then you can easily move on to more advanced or specialized topics such as deep learning, ML engineering, or other intriguing topics. This is definitely a great course to start with for beginners.
Provider: Andrew Ng, Stanford
Cost: Free to audit, $79 for Certificate
Rate: 4.9/5
Enroll here : https://tinyurl.com/yxytzcyy
