Introduction to Track A

Track A is for members to learn the fundamentals of Artificial Intelligence. The objective of the track is to enable ordinary people without AI background to apply AI to solve problems in the traditional Data Science. In the meantime, understanding the concepts, theory, and process in Machine Learning is the key to understand all the other areas in Artificial Intelligence.   

Prerequisites

The following Math knowledge is required to understand Machine Learning. However, the club will review the related parts of the Math subjects: 

  • Probability & Statistics
  • Statistics
  • Linear Algebra
  • Calculus

Main Contents

The members will learn the following knowledge and skills:
 
Supervised Learning and Unsupervised Learning
Feature
Classification Algorithms
Regression Algorithms
Support Vector Machines (SVM)
Clustering
Anomaly Detection
Recommender Systems
Dimensionality Reduction
Regularization
Machine Learning Pipelines 
AutoML
Machine Learning Applications
Machine Learning Model Training