Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
- natural-language-processing
- machine-learning
- named-entity-recognition
- machine-translation
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Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
TranslatedA Python web scraping tutorial series, learning Python web scraping from 0 to 1, including browser packet capture and mobile APP packet capture with tools such as fiddler and mitmproxy, the use of the various modules involved in web scraping, such as requests, beautifulSoup, selenium, appium, scrapy, etc., as well as IP proxies, CAPTCHA recognition, using Mysql and MongoDB databases with Python, multi-threaded and multi-process scraping, reverse engineering and cracking of CSS scraping encryption, JS scraping reverse engineering, distributed scraping, practical scraping project examples, etc.
Translated100-Days-Of-ML-Code Chinese version
🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools
Best Practices on Recommendation Systems
🤗 PEFT: State-of-the-art Parameter-Efficient Fine-Tuning.
☁️ Build multimodal AI applications with cloud-native stack
Translated⚡️HivisionIDPhotos: a lightweight and efficient AI ID photos tools. A lightweight AI algorithm for making ID photos.
Open standard for machine learning interoperability
💬 Open source machine learning framework to automate text- and voice-based conversations: NLU, dialogue management, connect to Slack, Facebook, and more - Create chatbots and voice assistants
🦉 OWL: Optimized Workforce Learning for General Multi-Agent Assistance in Real-World Task Automation
Train transformer language models with reinforcement learning.
Machine Learning Engineering Open Book
TranslatedAbu Quantitative Trading System (stocks, options, futures, Bitcoin, machine learning) An open-source quantitative trading and quantitative investment architecture based on Python
The absolute trainer to light up AI agents.
A scalable generative AI framework built for researchers and developers working on Large Language Models, Multimodal, and Speech AI (Automatic Speech Recognition and Text-to-Speech)
ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works with Claude Code, Codex, OpenClaw, or any LLM agent.
📚 Playground and cheatsheet for learning Python. Collection of Python scripts that are split by topics and contain code examples with explanations.
Private AI platform for agents, assistants and enterprise search. Built-in Agent Builder, Deep research, Document analysis, Multi-model support, and API connectivity for agents.
Code samples for my book "Neural Networks and Deep Learning"
🐫 CAMEL: The first and the best multi-agent framework. Finding the Scaling Law of Agents. https://www.camel-ai.org
Datasets, Transforms and Models specific to Computer Vision
A cd command that learns - easily navigate directories from the command line
OpenAI Baselines: high-quality implementations of reinforcement learning algorithms