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The Classiq Library is the largest collection of quantum algorithms and applications. It is the best way to explore quantum computing software. We welcome community contributions to our Library 🙌
Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://amzn.to/3JUgR2L
LangChain 공식 Document, Cookbook, 그 밖의 실용 예제를 바탕으로 작성한 한국어 튜토리얼입니다. 본 튜토리얼을 통해 LangChain을 더 쉽고 효과적으로 사용하는 방법을 배울 수 있습니다.
Official implementation for "Automatic Chain of Thought Prompting in Large Language Models" (stay tuned & more will be updated)
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Simple UI for LLM Model Finetuning
I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!
This repository showcases a selection of machine learning projects undertaken to understand and master various ML concepts. Each project reflects commitment to applying theoretical knowledge to practical scenarios, demonstrating proficiency in machine learning techniques and tools.
Official community-driven Azure Machine Learning examples, tested with GitHub Actions.
A replica of the AlphaZero methodology for deep reinforcement learning in Python
Let us democratise high-resolution generation! (CVPR 2024)
An automatic evaluator for instruction-following language models. Human-validated, high-quality, cheap, and fast.
[CVPR 2021] Official PyTorch implementation for Transformer Interpretability Beyond Attention Visualization, a novel method to visualize classifications by Transformer based networks.
InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation 🔥
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
Pytorch❤️ Keras 😋😋
Recipes for shrinking, optimizing, customizing cutting edge vision models. 💜
A concise, beginner-friendly introduction to the core ideas of linear algebra.
Implementation of all RL algorithms in a simpler way
Code, Notebooks and Examples from Practical Business Python
Udemy üzerindeki Python kurslarında kullanılan materyaller
Approaching (Almost) Any Machine Learning Problem中译版，在线文档地址：https://ytzfhqs.github.io/AAAMLP-CN/
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]
Pytorch implementations of Bayes By Backprop, MC Dropout, SGLD, the Local Reparametrization Trick, KF-Laplace, SG-HMC and more