https://github.com/rosa-lpz/machine-learning-handbook
Machine learning fundamentals and practical applications
https://github.com/rosa-lpz/machine-learning-handbook
machine-learning machine-learning-algorithms machine-learning-notes machine-learning-tutorials
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Machine learning fundamentals and practical applications
- Host: GitHub
- URL: https://github.com/rosa-lpz/machine-learning-handbook
- Owner: rosa-lpz
- License: mit
- Created: 2025-07-18T20:31:56.000Z (10 months ago)
- Default Branch: main
- Last Pushed: 2025-12-20T03:08:35.000Z (5 months ago)
- Last Synced: 2025-12-22T12:20:33.372Z (5 months ago)
- Topics: machine-learning, machine-learning-algorithms, machine-learning-notes, machine-learning-tutorials
- Language: Jupyter Notebook
- Homepage:
- Size: 5.4 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# Machine Learning Handbook
Machine Learning notes and tutorials
## Content
### Supervised Learning
#### Classification
#### [Regression](02_supervised_learning/regression/)
* [Linear Regression](02_supervised_learning/regression/linear-regression/)
### Unsupervised Learning
#### [Anomaly Detection](https://github.com/rosa-lpz/machine-learning-handbook/tree/86ab14e821cd6e104f310d0e1f1d59b3d0488efe/Unsupervised%20Learning/Anomaly%20Detection)
# What Is Machine Learning?
Machine learning is the science (and art) of programming computers so they can
learn from data.
Here is a slightly more general definition:
[Machine learning is the] field of study that gives computers the ability to learn
without being explicitly programmed.
—Arthur Samuel, 1959
And a more engineering-oriented one:
A computer program is said to learn from experience E with respect to some task
T and some performance measure P, if its performance on T, as measured by P,
improves with experience E.
—Tom Mitchell, 1997