This class is for students who don't know much about machine learning but are interested in learning the basic concepts.

This is for students who just started their journey in the field of Machine Learning.

In this class, I am going to cover the basic fundamentals of Machine Learning:

• What is Machine Learning?
• How Machine Learning is related to Animal/Human Learning?
• What is Machine Learning Algorithm and Model?
• Machine Learning Process.
• Types of Machine Learning Algorithms:
• Supervised Learning
• Classification: Binary and Multiclass Classification.
• Regression
• Unsupervised Learning
• Reinforcement Learning
• Evolutionary Learning.
• What is classification?
• Applications of Classification.
• Different approaches to Classification.
• Probabilistic Classifier
• Non-Probabilistic Classifier
• Some classification algorithms and their working.
• Bayes' Classifier
• K Nearest Neighbors Algorithm
• Decision Tree Algorithm
• How to measure the performance of a Classification Model.

This session is going to be pure basic hence anyone can attend.

Having knowledge of Datamining will be beneficial but not compulsory.