#python #artificial_intelligence #cloud_ml #computer_systems #courseware #deep_learning #edge_machine_learning #embedded_ml #machine_learning #machine_learning_systems #mobile_ml #textbook #tinyml

You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering.

https://github.com/harvard-edge/cs249r_book

#cplusplus #automatic_differentiation #large_language_models #machine_learning #tensor_algebra

GGML is a lightweight, efficient tensor library written in C that helps you run large machine learning models on everyday hardware like laptops, phones, and even Raspberry Pi. It supports integer quantization (reducing model size and speeding up processing), automatic differentiation, and works across many platforms without needing extra software. GGML uses zero memory allocation during runtime, which improves performance and is great for edge devices with limited resources. You can build and run models easily, including GPT-2, and it supports CUDA, Android, and other hardware. This means you can use advanced AI models faster and cheaper on your existing devices.

https://github.com/ggml-org/ggml

#python #agents #ai #ai_engineer #ai_engineering #copilot #data_science #data_scientist #generative_ai #gpt #machine_learning #ml_engineer #ml_engineering #openai

AI Data Science Team is a free Python library with AI agents that speed up your data work 10X by handling loading, cleaning, visualization, EDA, feature engineering, modeling, and SQL tasks. Its flagship AI Pipeline Studio app creates visual, reproducible pipelines you can run with Streamlit after easy install (Python 3.10+, OpenAI or Ollama). This saves you hours on repetitive jobs, boosts accuracy, and lets you focus on insights and business results.

https://github.com/business-science/ai-data-science-team

#python #agent #llm #llm_agent #llm_reasoning #machine_learning_systems #mlsys #reinforcement_learning #rl

AReaL is a free, open-source system for fast asynchronous reinforcement learning to train large AI models in math, coding, search, and agents. It decouples generation and training for up to 2.77x speedup, stable performance, and easy setup on single or 1000+ GPUs with algorithms like GRPO/PPO. Install via git/pip, run examples like GSM8K math instantly. You benefit by building top AI agents affordably and quickly, reproducing results with shared data/models, saving time/money vs. slow synchronous tools.

https://github.com/inclusionAI/AReaL

#python #bloomberg_terminal #contributions_welcome #finance #financial_markets #foss #good_first_issue #help_wanted #investing #investment #investment_research #machine_learning #opensource #python #quantitative_finance #stock_market #stocks

Fincept Terminal v4.0.2 is a free, open-source (AGPL-3.0) native C++20 desktop app with Qt6 UI and Python analytics, offering CFA-level tools like DCF models, portfolio optimization, risk metrics, 37 AI agents (Buffett-style to geopolitics), 100+ data connectors (Yahoo, FRED, brokers), real-time crypto/equity trading via 16 brokers, QuantLib suite, node editor workflows, and global intelligence. Download installers for Windows, Linux, macOS from GitHub releases or build easily with scripts/Docker. It benefits you by delivering Bloomberg-class performance in one fast binary, unlimited data access, and pro analytics to boost trading decisions and research without limits or high costs.

https://github.com/Fincept-Corporation/FinceptTerminal

#python #agents #ai #ai_agents #ai_engineering #computer_vision #course #deep_learning #from_scratch #generative_ai #llm #machine_learning #mcp #nlp #python #reinforcement_learning #rust #swarm_intelligence #transformers #tutorial #typescript

This is a free MIT learning guide for AI engineering with 428 lessons in 20 phases. It teaches you AI from the math up, then moves into machine learning, deep learning, LLMs, agents, tools, safety, and production. Each lesson helps you build useful code or AI tools, not just read theory. You can start at the right level, follow a clear path, and keep reusable artifacts for real work. The benefit is simple: you learn how AI actually works and gain practical skills you can use to build and ship better AI systems.

https://github.com/rohitg00/ai-engineering-from-scratch

#other #ai #artificial_intelligence #deep_learning #intelligent_machines #intelligent_systems #machine_intelligence #machine_learning #neural_network #reinforcement_learning #statistical_learning #unsupervised_learning

This is a curated AI roadmap with books, courses, papers, tools, and agents for learning and building modern AI systems. It helps you quickly find trusted resources for RAG, agents, evals, deployment, and coding tools, so you can learn faster and build better AI products with less guesswork.

https://github.com/owainlewis/awesome-artificial-intelligence

#typescript #ai_textbook #algorithms #artificial_intelligence #computer_science #computer_vision #deep_learning #jax #linear_algebra #machine_learning #machine_learning_algorithms #math #mathematics #multimodal_learning #nlp #probability #python #reinforcement_learning #speech_processing #statistics

This free, open textbook teaches math, computer science, and AI from the ground up by prioritizing intuition and real-world context over dense formulas, helping you deeply understand concepts instead of just passing exams . You only need basic math and Python to start, as the material connects all topics into a clear, logical flow designed for curious practitioners . The key benefit is that it gives you the quality knowledge needed to master complex AI roles, proven by friends who used these notes to get hired at top companies like DeepMind and OpenAI .

https://github.com/HenryNdubuaku/maths-cs-ai-compendium

#python #ai #assistant #language_model #machine_learning #python #speech #speech_synthesis #speech_to_text #speech_translation

I can help you build a fast, modular voice agent that turns speech into text, sends it to a language model, then speaks the answer back. It works with open-source or hosted models, can run fully local on your own hardware, and supports live transcription and low-latency conversation, so you get a flexible voice app that you can customize for speed, privacy, and different devices.

https://github.com/huggingface/speech-to-speech

#python #deep_face_swap #deep_learning #deep_neural_networks #deepface #deepfakes #deeplearning #face_swap #faceswap #fakeapp #machine_learning #myfakeapp #neural_nets #neural_networks #openfaceswap

FaceSwap is a computer tool that uses deep learning to recognize and swap faces in photos and videos, and it works best on Windows, Linux, or Mac with a modern GPU. You first extract faces, then train a model, then convert new images or video, so you can create face swaps or learn how AI face recognition works more easily.

https://github.com/deepfakes/faceswap