Cerebrum
Crossmodal Supervised Learning Toolkit using High-Performance Extreme Learning Machines over the audio-visual-textual data
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Self Driving Car In Video Games | 729 | 4 months ago | 2 | gpl-3.0 | Python | |||||
| A deep neural network that learns to drive in video games | ||||||||||
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| Official Implement of "ADBench: Anomaly Detection Benchmark". | ||||||||||
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| A TensorFlow-inspired neural network library built from scratch in C# 7.3 for .NET Standard 2.0, with GPU support through cuDNN | ||||||||||
| Neural Pipeline | 314 | 4 years ago | 19 | February 12, 2019 | 29 | mit | Python | |||
| Neural networks training pipeline based on PyTorch | ||||||||||
| Overcoming Catastrophic | 219 | 4 years ago | Jupyter Notebook | |||||||
| Implementation of "Overcoming catastrophic forgetting in neural networks" in Tensorflow | ||||||||||
| Shallowlearn | 196 | 7 years ago | 5 | December 30, 2016 | 17 | lgpl-3.0 | Python | |||
| An experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn. | ||||||||||
| Machine_learning_2018 | 146 | 3 years ago | 5 | Jupyter Notebook | ||||||
| Codes and Project for Machine Learning Course, Fall 2018, University of Tabriz | ||||||||||
| Ycml | 118 | 7 years ago | 5 | gpl-3.0 | Objective-C | |||||
| A Machine Learning and Optimization framework for Objective-C and Swift (MacOS and iOS) | ||||||||||
| Python Machine Learning Book 3rd Edition | 93 | 6 months ago | 2 | mit | Jupyter Notebook | |||||
| <머신 러닝 교과서 3판>의 코드 저장소 | ||||||||||
| Machine Learning Models | 81 | 7 years ago | 1 | Matlab | ||||||
| Decision Trees, Random Forest, Dynamic Time Warping, Naive Bayes, KNN, Linear Regression, Logistic Regression, Mixture Of Gaussian, Neural Network, PCA, SVD, Gaussian Naive Bayes, Fitting Data to Gaussian, K-Means | ||||||||||
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