golikeri's Stars
abhishekkrthakur/colabcode
Run VSCode (codeserver) on Google Colab or Kaggle Notebooks
abhishekkrthakur/approachingalmost
Approaching (Almost) Any Machine Learning Problem
KhronosGroup/OpenCL-CTS
The OpenCL Conformance Tests
HRNet/HRNet-Semantic-Segmentation
The OCR approach is rephrased as Segmentation Transformer: https://arxiv.org/abs/1909.11065. This is an official implementation of semantic segmentation for HRNet. https://arxiv.org/abs/1908.07919
fastai/fastbook
The fastai book, published as Jupyter Notebooks
karpathy/minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
microsoft/LightGBM
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
microsoft/Windows-Machine-Learning
Samples and Tools for Windows ML.
d2l-ai/d2l-en
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Black-Phoenix/Ai-Path-Tracer-Denoiser
This project is to create a CUDA accelerated Deep learning approach to denoise renders from a path tracer
intel/beignet
Beignet is an open source implementation of the OpenCL specification - a generic compute oriented API. Here is Beignet Source Code Mirror in github- This is a publish-only repository and all pull requests are ignored. Please follow https://wiki.freedesktop.org/www/Software/Beignet/ for any of your improvements
pranjalchaubey/Deep-Learning-Notes
My personal notes, presentations, and notebooks on everything Deep Learning.
pytorch/pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
alievk/avatarify-python
Avatars for Zoom, Skype and other video-conferencing apps.
TheAlgorithms/Python
All Algorithms implemented in Python
podgorskiy/ALAE
[CVPR2020] Adversarial Latent Autoencoders
eriklindernoren/ML-From-Scratch
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 learning.
fastai/numerical-linear-algebra
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
anhquan0412/basic_model_scratch
Implementation of some classic Machine Learning model from scratch and benchmarking against popular ML library
rwightman/gen-efficientnet-pytorch
Pretrained EfficientNet, EfficientNet-Lite, MixNet, MobileNetV3 / V2, MNASNet A1 and B1, FBNet, Single-Path NAS
kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
chiphuyen/python-is-cool
Cool Python features for machine learning that I used to be too afraid to use. Will be updated as I have more time / learn more.
ageron/handson-ml2
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
TianzhongSong/keras-FP16-test
Evaluating deep learning models with float16 dtype in Keras, float16 inference
aappleby/smhasher
Automatically exported from code.google.com/p/smhasher
XiaoMi/mace
MACE is a deep learning inference framework optimized for mobile heterogeneous computing platforms.
NVlabs/PL4NN
Perceptual Losses for Neural Networks: Caffe implementation of loss layers based on perceptual image quality metrics.
jonkhler/s2cnn
Spherical CNNs
Hvass-Labs/TensorFlow-Tutorials
TensorFlow Tutorials with YouTube Videos
amaas/stanford_dl_ex
Programming exercises for the Stanford Unsupervised Feature Learning and Deep Learning Tutorial