| pytorch/pytorch |
74,794 |
|
3,341 |
8,272 |
about 2 years ago |
39 |
November 15, 2023 |
13,261 |
other |
Python |
| Tensors and Dynamic neural networks in Python with strong GPU acceleration |
| jcjohnson/pytorch-examples |
4,170 |
|
0 |
0 |
about 4 years ago |
0 |
|
8 |
mit |
Python |
| Simple examples to introduce PyTorch |
| trekhleb/machine-learning-experiments |
1,552 |
|
0 |
0 |
over 2 years ago |
0 |
|
7 |
mit |
Jupyter Notebook |
| 🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo |
| ashishpatel26/Andrew-NG-Notes |
1,367 |
|
0 |
0 |
over 3 years ago |
0 |
|
2 |
|
Jupyter Notebook |
| This is Andrew NG Coursera Handwritten Notes. |
| SkalskiP/ILearnDeepLearning.py |
1,291 |
|
0 |
0 |
over 2 years ago |
0 |
|
24 |
mit |
Jupyter Notebook |
| This repository contains small projects related to Neural Networks and Deep Learning in general. Subjects are closely linekd with articles I publish on Medium. I encourage you both to read as well as to check how the code works in the action. |
| n2cholas/awesome-jax |
1,156 |
|
0 |
0 |
over 2 years ago |
0 |
|
12 |
cc0-1.0 |
|
| JAX - A curated list of resources https://github.com/google/jax |
| ahmedfgad/NumPyCNN |
531 |
|
0 |
0 |
almost 3 years ago |
3 |
May 24, 2018 |
1 |
|
Python |
| Building Convolutional Neural Networks From Scratch using NumPy |
| albertbup/deep-belief-network |
401 |
|
0 |
0 |
about 4 years ago |
0 |
|
13 |
mit |
Python |
| A Python implementation of Deep Belief Networks built upon NumPy and TensorFlow with scikit-learn compatibility |
| llSourcell/Convolutional_neural_network |
337 |
|
0 |
0 |
about 7 years ago |
0 |
|
7 |
|
Jupyter Notebook |
| This is the code for "Convolutional Neural Networks - The Math of Intelligence (Week 4)" By Siraj Raval on Youtube |
| jorgenkg/python-neural-network |
278 |
|
1 |
0 |
about 6 years ago |
4 |
July 29, 2016 |
5 |
bsd-2-clause |
Python |
| This is an efficient implementation of a fully connected neural network in NumPy. The network can be trained by a variety of learning algorithms: backpropagation, resilient backpropagation and scaled conjugate gradient learning. The network has been developed with PYPY in mind. |
