The presentation covers the basics of machine learning, a subset of artificial intelligence that enables computers to learn from data and experiences. It discusses three main types of learning: supervised learning with labeled data, unsupervised learning with unlabeled data, and reinforcement learning focused on decision-making for optimal rewards. Overall, it emphasizes the ability of machines to identify patterns and make predictions.

1. Presentation on
Machine Learning
Tahreem Suhail(22-BSIT-42)

2. Jens
Martensson
Machine learning is a science of getting computers to
learn and act like humans . It is a subset of artificial
intelligence (AI) that provides machines with the ability
to automatically learn from data and past experiences
while identifying patterns to make predictions
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3. Jens
Martensson
How it works?
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4. Jens
Martensson
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5. Jens
Martensson
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Supervised Learning
Supervised learning is the types of machine learning in which machines are trained using well
"labelled" training data, and on basis of that data, machines predict the output.

6. Jens
Martensson
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Unsupervised Learning
Unsupervised learning in artificial intelligence is a type of machine learning that learns from data
without human supervision. Unlike supervised learning, unsupervised machine learning models are
given unlabeled data and allowed to discover patterns and insights without any explicit guidance or
instruction.

7. Jens
Martensson
Reinforcement Learning (RL) is the science of decision making. It is about learning the optimal
behavior in an environment to obtain maximum reward. This optimal behavior is learned
through interactions with the environment and observations of how it responds
Reinforcement Learning
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8. Thank You
so much for your attention