Learn how to design, develop, deploy and iterate on production-grade ML applications.

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.

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

The fastai book, published as Jupyter Notebooks

A collection of various deep learning architectures, models, and tips

Python code for "Probabilistic Machine learning" book by Kevin Murphy

T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis

"Probabilistic Machine Learning" - a book series by Kevin Murphy

The "Python Machine Learning (3rd edition)" book code repository

A python tutorial on bayesian modeling techniques (PyMC3)

My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entr…

Efficient Python Tricks and Tools for Data Scientists

Companion site for the textbook Quantum Computing: An Applied Approach

A simple probabilistic programming language.

Jupyter notebooks associated with the Algorithms for Optimization textbook

Home for cuQuantum Python & NVIDIA cuQuantum SDK C++ samples

Bayesian neural network using Pyro and PyTorch on MNIST dataset

Lecture notebooks and coding assignments for the quantum machine learning MOOC created by Peter Wittek on EdX in the Spring 2019

Computer vision container that includes Jupyter notebooks with built-in code hinting, Anaconda, CUDA 11.8, TensorRT inference accelerator for Tensor cores, CuPy (GPU drop in replacement for Numpy),…

All of the code for my Medium articles

My attempt at researching Quantum Mechanics & Quantum Computing when I was a junior.

A Practical Guide to Quantum Machine Learning and Quantum Optimization, published by Packt

ICHEC Quantum natural language processing (QNLP) toolkit

QOSF mentorship related stuff

This repository implements the architecture proposed by Verdon et al. in the paper Learning to learn with quantum neural networks via classical neural networks, using PennyLane and TensorFlow.

QOSF mentorship program