Zach Bessinger's repositories
AI-DL-Enthusiasts-Meetup
AI & Deep Learning Enthusiasts Meetup Project & Study Sessions
CSML_notes
UCL MSc Computational Statistics and Machine Learning Revision Notes
datascience
Curated list of Python resources for data science.
DeeperInverseCompositionalAlgorithm
Taking a Deeper Look at the Inverse Compositional Algorithm (CVPR 2019, Oral)
DeepLearningFrameworks
Demo of running NNs across different frameworks
Detectron
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
faster_rcnn_pytorch
Faster RCNN with PyTorch
fourier_neural_operator
Use Fourier transform to learn operators in differential equations.
lectures-labs
Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay
ML-From-Scratch
Bare bones Python implementations of Machine Learning models and algorithms. Aims to cover everything from Data Mining techniques to Deep Learning.
MML-Book
Code / solutions for Mathematics for Machine Learning (MML Book)
NapkinML
A tiny lib with pocket-sized implementations of machine learning models in NumPy.
nn-transfer
Convert trained PyTorch models to Keras, and the other way around
np-to-tf-embeddings-visualiser
Quick function to go from a dictionary of sets of (images, labels, feature vectors) to checkpoints that can be opened in Tensorboard
PhotographicImageSynthesis
Photographic Image Synthesis with Cascaded Refinement Networks
PMS_Updater
Shell script for updating the Plex Media Server inside the FreeNAS Plex plugin
project-based-learning
Curated list of project-based tutorials
python-machine-learning-book-2nd-edition
The "Python Machine Learning (2nd edition)" book code repository and info resource
pytorch-CycleGAN-and-pix2pix
Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more)
relu_networks_overconfident
Why ReLU networks yield high-confidence predictions far away from the training data and how to mitigate the problem [CVPR 2019, oral]
stanford-cs-230-deep-learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
tutorials-and-papers
Collection of tutorials, exercises and papers on RL
youCanCodeAGif
Can you make an High Quality Gif from A to Z only by coding? Yes. Do you want to, though?