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Tensors and Dynamic neural networks in Python with strong GPU acceleration
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
Python sample codes and textbook for robotics algorithms.
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
Minimal and clean examples of machine learning algorithms implementations
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Fast, modular reference implementation of Instance Segmentation and Object Detection algorithms in PyTorch.
A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch
A PyTorch implementation of EfficientNet
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
A TensorFlow implementation of DeepMind's WaveNet paper
Image augmentation library in Python for machine learning.
Count the MACs / FLOPs of your PyTorch model.
A PyTorch Library for Accelerating 3D Deep Learning Research
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
📀 Unlimited Google Drive Storage by splitting binary files into base64
Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.
Modularized Implementation of Deep RL Algorithms in PyTorch
Fully Convolutional Networks for Semantic Segmentation by Jonathan Long*, Evan Shelhamer*, and Trevor Darrell. CVPR 2015 and PAMI 2016.
FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)
End-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
A pytorch implementation of Detectron. Both training from scratch and inferring directly from pretrained Detectron weights are available.