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Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Learn how to design, develop, deploy and iterate on production-grade ML applications.
Fast and Easy Infinite Neural Networks in Python
PyTorch implementation of various methods for continual learning (XdG, EWC, SI, LwF, FROMP, DGR, BI-R, ER, A-GEM, iCaRL, Generative Classifier) in three different scenarios.
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 compu…
The purpose of this repo is to make it easy to get started with JAX, Flax, and Haiku. It contains my "Machine Learning with JAX" series of tutorials (YouTube videos and Jupyter Notebooks) as well a…
A Software Framework for Neuromorphic Computing
Complete deep learning project developed in Full Stack Deep Learning, 2022 edition. Generated automatically from https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2022
QED-C: The Quantum Economic Development Consortium provides these computer programs and software for use in the fields of quantum science and engineering.
We implement a quantum-classical hybrid QLSTM model by incorporating quantum variational layers into the classical LSTM in order to improve the efficiency and trainability of LSTM for better stock …
Quantum Transformers for High Energy Physics Analysis at the Large Hadron Collider
A collection of guidelines to run quantum optimization algorithms on superconducting qubits with Qiskit, using as reference the Quantum Approximate Optimization Algorithm (QAOA) workflow.