https://github.com/jldbc/tensorflow_ml_algorithms
Implementations of machine learning algorithms in Tensorflow: MLP, RNN, autoencoder, PageRank, KNN, K-Means, logistic regression, and OLS regression
https://github.com/jldbc/tensorflow_ml_algorithms
algorithms autoencoder machine-learning-algorithms pagerank tensorflow
Last synced: 9 months ago
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Implementations of machine learning algorithms in Tensorflow: MLP, RNN, autoencoder, PageRank, KNN, K-Means, logistic regression, and OLS regression
- Host: GitHub
- URL: https://github.com/jldbc/tensorflow_ml_algorithms
- Owner: jldbc
- Created: 2016-12-27T00:59:12.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2017-01-24T05:17:17.000Z (over 9 years ago)
- Last Synced: 2025-05-07T19:47:36.821Z (12 months ago)
- Topics: algorithms, autoencoder, machine-learning-algorithms, pagerank, tensorflow
- Language: Python
- Homepage:
- Size: 12.7 KB
- Stars: 54
- Watchers: 6
- Forks: 22
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# Machine Learning Algorithms, Implemented in TensorFlow
This is a repository of ML algorithms I have implemented in TensorFlow. The goal of this project was
1. To implement these algorithms from a low level, in order to better understand them
2. To learn TensorFlow at a deeper level than basic tutorials would allow
I would highly recommend this task to anybody seeking to accomplish either objective.
The algorithms implemented are:
* OLS (Ordinary Least Squares Regression)
* Logit (Logistic Regression)
* KMeans (K-Means Clustering)
* KNN (K-Nearest Neighbors)
* PageRank (Google's algorithm for ranking search results)
* MLP (Multilayer Perceptrion - a Basic Feed-Forward Neural Network)
* Autoencoder
* RNN (Recurrent Neural Network)
My hope is to continue adding algorithms and improving these implementations with time.