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About Lecture1 PDF
The document is a lecture on machine learning. It defines machine learning as the ability of computers to learn from data and past experience to make predictions or decisions. It discusses different types of machine learning including supervised learning (using labeled examples to learn functions that map inputs to outputs), unsupervised learning (discovering patterns in unlabeled data like clustering), and reinforcement learning. Examples of applications like image recognition and game playing are provided. The lecture also covers course logistics like prerequisites, evaluation, and academic integrity policy.
Detailed Information
| Author: | ['Himanshu tripathi'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 37 |
| Language: | English |
| Format: | |
| Price: | FREE |
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