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

Updated and most comprehensive Repository On Quantum Computing Resources. It contains all the material I use for my research on Quantum Computing for Both Theories and Codes - I update it regularly.

👾 resources and experiments for autonomous agents (e.g., language models, reinforcement learning, energy based models)

Auto do tasks, play games, referrals, checkin.

收集量子机器学习的基础、算法、学习、项目等资料的收集。Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

This repository contains the code to reproduce the results in the paper "A Variational Algorithm for Quantum Single Layer Perceptron" submitted to The 8th International Online & Onsite Conference on Machine Learning, Optimization, and Data Science

My session about TensorFlow Quantum to build hybrid quantum-classical models at TensorFlow User Group Mysuru 2020

AI_Research_Junction@Aditi_Khare - Research Papers Summaries Capturing Latest advancements in Generative AI, Quantum AI and Computer Vision

Deep Q-Learning with Hybrid Quantum Neural Network on Solving Maze Problems

Building an OpenSource repo for guiding NOOBS --to-> PRO in QuantumAI 🚀

QRLIT: Quantum Reinforcement Learning for Database Index Tuning

Natural Language Qu Kit (NLQK)

An advanced AI application integrating quantum computing capabilities with deep learning frameworks to create powerful hybrid classical-quantum AI models. This technology aims to unlock new applications in fields such as chemistry, materials science, drug discovery, finance, and cryptography.

Quantum-ML is a hybrid quantum-classical machine learning project leveraging quantum computing and AI to deliver advanced predictions and solutions through a fast API interface.

🚀 QIP-X Framework – Quantum-Integrated AI & Cryptography A cutting-edge framework integrating quantum-ascendant cryptography, timeline optimization, and hyper-chaotic neural networks for secure, adaptive, and multiversal intelligence systems.

DEMO ~

Q-Learning Implementation for Process Optimization A reinforcement learning project that calculates the shortest route between locations using the Q-Learning algorithm. This code demonstrates how AI can optimize processes in a simulated environment with predefined states and rewards. 🚀