gradient-descent-methods-in-machine-learning
https://github.com/cedholm/gradient-descent-methods-in-machine-learning
Science Score: 44.0%
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Low similarity (3.8%) to scientific vocabulary
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Basic Info
- Host: GitHub
- Owner: cedholm
- Language: Jupyter Notebook
- Default Branch: main
- Size: 4.29 MB
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- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
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· Last pushed over 2 years ago
Metadata Files
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Citation
README.md
Gradient-descent-methods-in-machine-learning
This repository is associated with the chapter titled Gradient Descent Methods in Machine Learning in the book Cross-Curricular Applications for Pure Mathematics Courses.
Lesson 0 is about how to install Python on your computer using Anaconda for the Jupyter Notebooks utilized in Lessons 2-4.
Lesson 2 has code to find the minimum of a paraboloid using gradient descent.
Lesson 3 has code for a linear regression with gradient descent.
Lesson 4 has code for a logistic regression with gradient descent.
Data for each lesson is included in its particular folder.
Owner
- Name: Christina Edholm
- Login: cedholm
- Kind: user
- Location: Claremont, CA
- Company: Scripps College
- Website: www.cedholm.com
- Repositories: 1
- Profile: https://github.com/cedholm
Citation (CITATION.cff)
cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- family-names: Edholm
given-names: Christina
- family-names: Hohn
given-names: Maryann
- family-names: Radunskaya
given-names: Ami
title: "Gradient Descent Methods in Machine Learning"
date-released: 2022-2-22
url: "https://github.com/cedholm/Gradient-descent-methods-in-machine-learning"