Popular GitHub Repositories for Clean Tweets

Minimal and clean examples of machine learning algorithms implementations

A clean implementation based on AlphaZero for any game in any framework + tutorial + Othello/Gobang/TicTacToe/Connect4 and more

StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

.NET, Angular, Clean Architecture, Clean Code, SOLID Principles, KISS Principle, DRY Principle, Fail Fast Principle, Common Closure Principle, Common Reuse Principle, Acyclic Dependencies Principle, Mediator Pattern, Result Pattern, Folder-by-Feature Structure, Separation of Concerns

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

Label, clean and enrich text datasets with LLMs.

All-in-one productivity app and AI assistant with Tasks, Notes, Calendar, Diary and Bookmarks.

Clean PyTorch implementations of imitation and reward learning algorithms

Extract clean data from anywhere, powered by vision-language models ?

LangChain & Prompt Engineering tutorials on Large Language Models (LLMs) such as ChatGPT with custom data. Jupyter notebooks on loading and indexing data, creating prompt templates, CSV agents, and using retrieval QA chains to query the custom data. Projects for using a private LLM (Llama 2) for chat with PDF files, tweets sentiment analysis.

A practical architecture styles for migrating from legacy monolith to modern cloud native application with the latest technologies and architectures like Vertical Slice Architecture, Event Sourcing, CQRS, DDD, gRpc, MongoDB, RabbitMq, and Masstransit in .Net 9.

Stable Diffusion AI client app for Android

? A practical and imaginary food delivery microservices, built with .Net 8, MassTransit, Domain-Driven Design, CQRS, Vertical Slice Architecture, Event-Driven Architecture, and the latest technologies.

Stock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

A personal news aggregator to pull information from multi-sources + LLM (ChatGPT/Gemini/Ollama via LangChain) to help us reading efficiently with less noises, the sources including: Tweets, RSS, YouTube, Web Articles, Reddit, and personal Journal notes.

BERTweet: A pre-trained language model for English Tweets (EMNLP-2020)

???♂? Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.

A modern web-based metadata editor for audio files, designed for managing large music collections with clean bulk editing capabilities.

Minimal and clean examples of machine learning algorithms implemented in Julia