https://github.com/thomasnield/kotlin-machine-learning-demos
Demonstration of several machine learning algorithms in Kotlin
https://github.com/thomasnield/kotlin-machine-learning-demos
deep-learning kotlin logistic-regression machine-learing-algorithms machine-learning
Last synced: about 1 month ago
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Demonstration of several machine learning algorithms in Kotlin
- Host: GitHub
- URL: https://github.com/thomasnield/kotlin-machine-learning-demos
- Owner: thomasnield
- Created: 2019-05-20T02:16:42.000Z (almost 6 years ago)
- Default Branch: master
- Last Pushed: 2019-09-22T03:03:48.000Z (over 5 years ago)
- Last Synced: 2025-03-22T18:11:21.717Z (about 1 month ago)
- Topics: deep-learning, kotlin, logistic-regression, machine-learing-algorithms, machine-learning
- Language: Kotlin
- Homepage:
- Size: 5.76 MB
- Stars: 58
- Watchers: 4
- Forks: 7
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Showcases of Different ML Algorithms
### Using Background Color Classification
This is a Kotlin application that experiments with different machine learning algorithms to recommend a light/dark font against different background colors.
Some algorithms are built completely from scratch but others are showcased using a library.
The current algorithms/library implementations:
- Formulaic
- Linear regression (w/ hill climbing)
- Logistic regression (w/ hill climbing)
- Decision Tree
- Random Forest
- Neural Network (w/ hill climbing)
- Neural Network (w/ simulated annealing)
- OjAlgo Neural Network
- DL4J Neural Network
Planned to be added:
- Linear regression (w/ gradient descent)
- Logistic regression (w/ gradient descent)
- Continuous Naive Bayes
