This repository includes all my programming assignment submissions to the Machine learning course offered by Stanford University in Coursera.
I was so glad to be enrolled in this course and to be a student of Andrew Ng. It took me almost 3 months to complete the course with a grade of 95 percent.
The course equipped me with knowledge and practical skills on various topics, which include:
- Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks).
- Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning).
- Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI)
The course also draw intutions from numerous case studies and applications, so as to learn how to apply learning algorithms to build applications such as:
- smart robots (perception, control)
- text understanding (web search, anti-spam)
- computer vision
- medical informatics
- audio
- database mining