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About (Machine Learning Coursera) Lecture Note Week 1
The document provides an introduction to machine learning concepts including: 1) Two definitions of machine learning are given that describe it as either giving computers the ability to learn without explicit programming, or improving performance on tasks through experience. 2) Machine learning problems are classified as either supervised learning, involving labeled training data, or unsupervised learning without labeled data. 3) Supervised learning is further divided into regression to predict continuous outputs and classification to predict discrete categories. Unsupervised learning clusters data to derive structure without labels. 4) Linear regression for a single variable is described, using a hypothesis function of y=θ0+θ1x to model the data fitted by a cost function minimized through gradient
Detailed Information
| Author: | ['JonnyJack'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 8 |
| Language: | English |
| Format: | |
| Price: | FREE |
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