Popular GitHub Repositories for Quantum Bias

Fit interpretable models. Explain blackbox machine learning.

Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry, Materials Science and Biology

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

PennyLane is a cross-platform Python library for quantum computing, quantum machine learning, and quantum chemistry. Train a quantum computer the same way as a neural network.

A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

A library of enterprise-grade AI agents designed to democratize artificial intelligence and provide free, open-source alternatives to overvalued Y Combinator startups. If you are excited about democratizing AI access & AI agents, please star ⭐️ this repository and use the link in the readme to join our open source AI research team.

Some awesome AI related books and pdfs for learning and downloading, also apply some playground models for learning

A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers.

Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry through innovation, reduce human bias in the modeling process & build a strong open source marketing science community.

XAI - An eXplainability toolbox for machine learning

Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)

SchNetPack - Deep Neural Networks for Atomistic Systems

Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.

Curated list of open source tooling for data-centric AI on unstructured data.

Machine learning algorithms for many-body quantum systems

A Benchmark of Text Classification in PyTorch

Notes for Deep Learning Specialization Courses led by Andrew Ng.

Accurate Neural Network Potential on PyTorch

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Explainable AI framework for data scientists. Explain & debug any blackbox machine learning model with a single line of code. We are looking for co-authors to take this project forward. Reach out @ ms8909@nyu.edu