https://github.com/diable201/machine-learning
Machine Learning Course Fall 2023 MSc
https://github.com/diable201/machine-learning
jupyter-notebook machine-learning python
Last synced: 3 months ago
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Machine Learning Course Fall 2023 MSc
- Host: GitHub
- URL: https://github.com/diable201/machine-learning
- Owner: diable201
- License: mit
- Created: 2023-12-30T17:27:12.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2024-01-01T10:21:17.000Z (over 2 years ago)
- Last Synced: 2025-03-11T04:32:45.635Z (over 1 year ago)
- Topics: jupyter-notebook, machine-learning, python
- Language: Jupyter Notebook
- Homepage:
- Size: 659 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
- License: LICENSE
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README
# Machine Learning
## COURSE OBJECTIVES
The objective of this course is to provide the student with the fundamental knowledge and skills in
the field of modern machine learning.
## COURSE OUTCOMES
At the end of the course and having completed the essential reading and activities students should be
able to:
* develop an understanding of the process to learn from data
* be familiar with a wide variety of algorithmic and model based methods to extract information from
data
* apply and evaluate suitable methods to various datasets by model selection and predictive
performance evaluation
* gain knowledge and experience on conducting machine learning in Python
## COURSE PREREQUISITES
* Basic programming experience with Python
* Basic concepts of linear algebra: vectors and matrices and operations on them
* Single and multivariate calculus topics such as derivatives and integrals
* Key notions of probability and statistics
## LITERATURE
1. James G., Witten D., Hastie T., Tibshirani R. and J. Taylor. An introduction to Statistical Learning: with
Applications in Python (2023).
1. Bishop C.M. Pattern recognition and machine learning. Springer (2006)
2. Murphy K.P. Machine learning: A probabilistic perspective. MIT Press, second edition (2012)