The document provides an overview of machine learning, defining it as a branch of artificial intelligence focused on data and algorithms that mimic human learning. It discusses three main types of machine learning: supervised learning, where algorithms use labeled data to make predictions; unsupervised learning, which analyzes unlabeled data to find patterns; and reinforcement learning, which optimizes decision-making for maximum rewards. Additionally, it highlights various applications for these machine learning techniques.

2. TOPICS:
WHAT IS MACHINE LEARNING
TYPES OF ALGORITHMS
WHAT ARE THE APPLICATIONS
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3. what is machine learning
 It is a branch of Artificial intelligence and computer science which
focuses on the use of data and algorithms to imitate the way that
humans learn,gradually improving its accuracy

4. TYPES OF MACHINE LEARNING
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5. Supervised learning
 It is a method that involves learning using labeled past data
and the algorithm shall predict the label for unseen or future
data

6. Examples :
 Trying your shoes any step
by step process that is
completed the same way
every time is an algorithm
 Classifying objects
 Finding a library book in
library
 Deciding what to eat
 Driving to or from
somewhere

7.  Unsupervised learning
 IT uses machine learning algorithms to analyze and cluster unlabeled
data sets
 These algorithms discover hidden patterns or data groupings without the
need for human intervention

8.  Unsupervised learning

9.  Difference b/w supervised &
unsupervised learning

10.  Reinforcement learning
 It is the science of decision making
 It is about learning the optimal behaviour in an environment
to obtain maximum reward
EXAMPLE: how a robotic dog learns the movement of his
arms is an example of reinforcement learning

11.  How it works

12.  Applications

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