Popular GitHub Repositories for Aws Step Functions

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

Enhanced ChatGPT Clone: Features Agents, DeepSeek, Anthropic, AWS, OpenAI, Assistants API, Azure, Groq, o1, GPT-4o, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active project.

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

Gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls)

structured outputs for llms

Example ? Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using ? Amazon SageMaker.

Build, Manage and Deploy AI/ML Systems

Experience, Learn and Code the latest breakthrough innovations with Microsoft AI

AI suite powered by state-of-the-art models and providing advanced AI/AGI functions. It features AI personas, AGI functions, multi-model chats, text-to-image, voice, response streaming, code highlighting and execution, PDF import, presets for developers, much more. Deploy on-prem or in the cloud.

Flexible and powerful framework for managing multiple AI agents and handling complex conversations

✨ AI agents that spark joy

Probabilistic time series modeling in Python

? Super-scale your images and run experiments with Residual Dense and Adversarial Networks.

Kodu is an autonomous coding agent that lives in your IDE. It is a VSCode extension that can help you build your dream project step by step by leveraging the latest technologies in automated coding agents

Accompanying source code for Machine Learning with TensorFlow. Refer to the book for step-by-step explanations.

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Climate / Energy, Automotives, Retail, Pharma, Medicine, Healthcare, Policy, Ethics and more.

The LLM's practical guide: From the fundamentals to deploying advanced LLM and RAG apps to AWS using LLMOps best practices

The leading workflow orchestration platform. Run stateful step functions and AI workflows on serverless, servers, or the edge.

? ????? about ????, ??????, and ?????? ??? for free by designing, training, and deploying a real-time financial advisor LLM system ~ ?????? ???? + ????? & ??????? ?????????

? Turns your machine learning code into microservices with web API, interactive GUI, and more.