Machine learning list

Intro

These are project i want to do a little bit more with, about machine learning

Programming

• Machine learning course
• AI note taking app that runs locally
• Build you’re first machine learning model with python in 7 minutes
• Awesome machine learning curated list
• Python OpenAI projects
• Curated List op Chatgtp resources
• A curated list of all things awesome about OpenAI - the research company behind ChatGPT
• TTS Tortoise
• Ollama language models
• Hugging faces
• OpenWebUI
• litellm.ai docs github litelmm
• weaviate recipes
• dspy prompt automater videos
• openui build ui using llm
• Instructor is a Python library that makes it a breeze to work with structured outputs from large language models
• Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust.
• chromadb the AI-native open-source embedding database
• open webui pipelines
• gradio web interfaces
• Build a Large Language Model from Scratch
• Awesome LLM Apps
• Embedchain streamlines deploying personalized LLM apps in production
• PydanticAI Examples
• code2prompt
• Aider is AI pair programming in your terminal
• Pathway AI Pipelines
• Anon-kode: Terminal-based AI coding tool that can use any model that supports the OpenAI-style API.

Urls

• Cleaning data with ai
• Prompts for cleaning processing data with ai
• Ai prompts for web designers and developers
• Awesome Generative Ai
• Continue, The easiest way to code with any LLM
• Subsai subtitles
• Markdowner : A fast tool to convert any website into LLM-ready markdown data.
• skyvern Automate browser-based workflows using LLMS and computer vision.
• learnbybuilding.ai dspy youtube
• groqcloud : Free cloud for llama based api
• fabric is an open-source framework for augmenting humans using AI.
• powerproxy
• chromadb
• langchain quickstart
• livePortrait Efficient Portrait Animation with Stitching and Retargeting Control
• llm router Building an LLM Router for High-Quality and Cost-Effective Responses
• anything LLM
• GeAi_Agents
• Haystack
• hallo2 audio-driven portrait image animation
• Skyvern automates browser-based workflows using LLMs
• Rocketnotes is a web-based Markdown note taking app with LLM
• Open Interpreter lets LLMs run code (Python, Javascript, Shell, and more) locally.
• OpenR: Advanced Reasoning with Large Language Models
• Agent S: An Open Agentic Framework that Uses Computers Like a Human
• gptme: Personal AI assistant in your terminal
• browser-use: Let LLMs interact with websites through a simple interface.
• Autoflow: An open source GraphRAG (Knowledge Graph) built on top of TiDB Vector and LlamaIndex and DSPy. github

Need to try

• vscode huggingface
• LLM 101: Build your own book-reading bot or search engine with LLM (RAG)
• suno-bark: ai text to audio
• DeepResearch: Keep searching and reading webpages until finding the answer

Books

• [https://github.com/HandsOnLLM/Hands-On-Large-Language-Models](O’Reilly Hands-On Large Language Models)

Variants

• open-webui
• litellm-proxy

Prompts

gen ai export

you a a gen ai expert, you can create prompts to let a gen ai answer everthing, in the prompt you take care of all the details

Gen ai export datascience prompt generator

"You are an expert in crafting prompts for generative AI models for tasks involving data formation, cleaning, processing, analysis, and visualization. Your expertise lies in understanding the critical data handling processes and translating them into clear, step-by-step prompts that AI models can effectively execute.

When approaching a data-related task, you prioritize understanding the precise requirements, identifying any potential issues or constraints, and planning a systematic approach. You have in-depth knowledge of data formats, schemas, cleaning techniques, feature engineering methods, statistical analyses, and visualization best practices.

Your prompts should guide the AI through each stage of the data workflow, ensuring that proper data hygiene, integrity checks, and validation steps are incorporated. You emphasize the importance of documenting assumptions, handling missing or inconsistent data, and maintaining reproducibility.

For data analysis and modeling tasks, your prompts should cover exploratory data analysis, feature selection, model training and evaluation processes, as well as techniques for interpreting and communicating results effectively.

Throughout the process, you underscore the significance of following industry-standard practices, adhering to ethical guidelines, and maintaining data privacy and security where applicable.

Your goal is to create prompts that are comprehensive, technically sound, and aligned with the principles of responsible data science. You guide the AI to approach data tasks with rigor, attention to detail, and a commitment to delivering high-quality, actionable insights."

This prompt establishes the AI's role as an expert in data science prompting, highlights the critical processes involved, and emphasizes the importance of following best practices, maintaining data integrity, and adhering to ethical standards. It instructs the AI to create prompts that are technically sound, thorough, and focused on delivering high-quality, actionable insights through responsible data handling and analysis.