Pinned Repositories
data-science-ipython-notebooks
Continually updated Data Science Python Notebooks: Spark, Hadoop MapReduce, HDFS, AWS, Kaggle, scikit-learn, matplotlib, pandas, NumPy, SciPy, and various command lines.
Kalman-and-Bayesian-Filters-in-Python
Kalman Filter textbook using Ipython Notebook. This book takes a minimally mathematical approach, focusing on building intuition and experience, not formal proofs. Includes Kalman filters, Extended Kalman filters, unscented filters, and more. Includes exercises with solutions.
WKU-Pathfinder
zbessinger's Repositories
zbessinger/AI-DL-Enthusiasts-Meetup
AI & Deep Learning Enthusiasts Meetup Project & Study Sessions
zbessinger/CSML_notes
UCL MSc Computational Statistics and Machine Learning Revision Notes
zbessinger/datascience
Curated list of Python resources for data science.
zbessinger/DeeperInverseCompositionalAlgorithm
Taking a Deeper Look at the Inverse Compositional Algorithm (CVPR 2019, Oral)
zbessinger/DeepLearningFrameworks
Demo of running NNs across different frameworks
zbessinger/Detectron
FAIR's research platform for object detection research, implementing popular algorithms like Mask R-CNN and RetinaNet.
zbessinger/face_inpainting
zbessinger/faster_rcnn_pytorch
Faster RCNN with PyTorch
zbessinger/fourier_neural_operator
Use Fourier transform to learn operators in differential equations.
zbessinger/kepler.gl
zbessinger/lectures-labs
Slides and Jupyter notebooks for the Deep Learning lectures at M2 Data Science Université Paris Saclay
zbessinger/Mask_RCNN
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow
zbessinger/minGPT
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
zbessinger/ML-From-Scratch
Bare bones Python implementations of Machine Learning models and algorithms. Aims to cover everything from Data Mining techniques to Deep Learning.
zbessinger/MML-Book
Code / solutions for Mathematics for Machine Learning (MML Book)
zbessinger/NapkinML
A tiny lib with pocket-sized implementations of machine learning models in NumPy.
zbessinger/nn-transfer
Convert trained PyTorch models to Keras, and the other way around
zbessinger/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
zbessinger/PhotographicImageSynthesis
Photographic Image Synthesis with Cascaded Refinement Networks
zbessinger/PMS_Updater
Shell script for updating the Plex Media Server inside the FreeNAS Plex plugin
zbessinger/project-based-learning
Curated list of project-based tutorials
zbessinger/python-machine-learning-book-2nd-edition
The "Python Machine Learning (2nd edition)" book code repository and info resource
zbessinger/pytorch-CycleGAN-and-pix2pix
Image-to-image translation in PyTorch (e.g. horse2zebra, edges2cats, and more)
zbessinger/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]
zbessinger/SNNs
Tutorials and implementations for "Self-normalizing networks"
zbessinger/stanford-cs-230-deep-learning
VIP cheatsheets for Stanford's CS 230 Deep Learning
zbessinger/t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
zbessinger/tutorials-and-papers
Collection of tutorials, exercises and papers on RL
zbessinger/youCanCodeAGif
Can you make an High Quality Gif from A to Z only by coding? Yes. Do you want to, though?
zbessinger/zbessinger.github.io