Skip to content

Latest commit

 

History

History
28 lines (16 loc) · 945 Bytes

File metadata and controls

28 lines (16 loc) · 945 Bytes

Machine-Learning

Created by Standford University.

Instructor: Andrew Ng

Contents

  • Lectures Slides
  • My Solutions to Programming Assignments Implemented in MATLAB

Introduction

This course explicitly explained the basics of machine learning, data mining, and statistical pattern recognition.

Topics include:

  1. Supervised Learning: Linear Regression, Logistic Regression, Support Vector Machines (SVM), Kernels, Neural networks.

  2. Unsupervised Learning: Clustering, Dimensionality Reduction, Anomaly Detection, Recommender systems

  3. Best Practices in Machine Learning: Bias/Variance theory; Innovation Process in Machine Learning and AI.

References

[1] Machine Learning - Stanford University

Certification

Certificate