Machine learning is a branch of artificial intelligence that allows programs and systems to learn automatically from empirical data and experience without being explicitly programmed. There are three main types of learning: supervised learning which uses labeled data to predict unlabeled items, unsupervised learning which finds hidden patterns in unlabeled data through clustering and reinforcement learning which allows machines to learn ideal behaviors through reward feedback to maximize performance. Reinforcement learning provides simple reward signals for agents to learn from without a label.

1. Machine Learning
Inspired from human learning!
Sandeep Karthikeyan

2. Domainof ML

3. WhatisML?
 1. Branch of Artificial Intelligence.
 2. ML concerns with the ability for
programs/systems to learn automatically from
empirical data without being explicitly
programmed.

4. Typesof
learning
 1. Supervised learning
 2. Unsupervised learning
 3. Reinforcement learning

5. Supervised
Learning

6. Modelthatcan
predictan
unlabeleditem

7. Unsupervised
learning ->
Learning without
aLabel

8. Onemore
example
(Clustering)

9. Reinforcement
Learning
 Reinforcement allows machines and software agents to
automatically determine the ideal behavior within a
specific context, in order to maximize its performance.
 Simple reward feedback is required for the agent to
learn its behavior; this is known as the reinforcement
signal.

10. MoreExamples

11. WhyMachine
Learning?

12. Questions?