It is a simple introduction to Machine Learning.

1. Machine Learning
Sahar Nasiri
Date: 26/1/96

2. What is Machine Learning
• Subfield of Artificial Intelligence (AI)
• Name is derived from the concept that it deals with
“construction and study of systems that can learn from data”
• Can be seen as building blocks to make computers learn to
behave more intelligently
• It is a theoretical concept. There are various techniques with
various implementations.
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3. General Categories
• Supervised Learning
• Unsupervised Learning
• Reinforcement Learning
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4. Supervised Learning
In supervised learning, we are given a data set and already know what our
correct output should look like, having the idea that there is a relationship
between the input and the output.
• Regression
• Classification
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5. Unsupervised Learning
Unsupervised learning allows us to approach problems with little or no idea
what our results should look like. We can derive structure from data where
we don't necessarily know the effect of the variables.
• Clustering
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6. General Categories
• Supervised Learning
• Supervised Learning
•Reinforcement Learning
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7. Machine Learning Applications
• Spam Email Detection
• Machine Translation (Language Translation)
• Image Search (Similarity)
• Clustering (K-Means) : Amazon Recommendations
• Classification : Google News
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8. The End