FELIPEACASTRO/AIForge

A coleção definitiva e curada de recursos de Inteligência Artificial (AI), Machine Learning (ML) e Deep Learning (DL). Inclui frameworks, modelos, datasets, MLOps, LLMs e aplicações financeiras/comerciais.

Jupyter Notebook

231 commits

updated Aug 15, 2026

See the code

README

AIForge — The Definitive Repository for AI, ML, and Data Science

AIForge is a comprehensive, hand-organized atlas of the Artificial Intelligence, Machine Learning, Deep Learning, LLM, and Data Science ecosystem — from foundational theory to production deployment and industry verticals.

2,200+ documents · 100% English · every directory carries an index README with keywords · a complete sitemap.xml (2,700+ URLs) covers every folder and file — built for maximum search-engine and LLM discoverability.

🚀 Start Here: Frontier AI 2026

00_FRONTIER_AI_2026 — a living Innovation Radar of the newest releases (GPT-5.5, Claude Opus 4.7 / Fable 5, DeepSeek V4, Qwen 3.7, Llama 4, Sora 2, Veo 3.1, GR00T N1.7, SGLang, AI-for-math) captured June 2026. This is the "what just shipped" layer; the 5 pillars below are the stable, organized core.

Five Pillars

#	Pillar	What lives here
01	AI Fundamentals & Theory	Foundational ML/DL theory, algorithms, paradigms (RL, GenAI, Transformers, SSMs), training methods, safety, evaluation.
02	LLM & AI Models	Frontier LLMs, open-source models, vision/audio/video/multimodal models, MoE, diffusion, world models, frameworks.
03	Datasets, Tools & Resources	Curated datasets by modality, data engineering, storage & databases, cloud, global AI ecosystem coverage, HuggingFace Hub, research/preprint platforms.
04	MLOps & Production AI	Model serving, LLM inference (vLLM/SGLang/TensorRT-LLM/llama.cpp), MLOps platforms, observability, deployment.
05	Vertical Applications	Industry-specific AI + Kaggle competitions & winning solutions: Healthcare, Banking (KYC/onboarding, AML, fraud), Financial Markets (stocks, options, futures, bonds, FX, crypto, quant trading), Agriculture, Robotics, AV, more.

How to Navigate

Browse by pillar. Each pillar has a sub-tree of canonical, English, snake_case topics — no duplicates, no language drift.

Use INDEX.md. The complete sitemap with every category and a one-line description.

Use NAVIGATION_GUIDE.md. A topic-first guide ("I want to learn about RAG" → exact path).

Track enrichment. The repo-wide directory enrichment pass is recorded in docs/DIRECTORY_ENRICHMENT_RUN_2026-07-07.md, and broad AI/ML source routing lives in AI_ML_Data_Model_Prompt_Source_Atlas_Batch_01_2026-07-07.md.

GitHub search. Scoped path search: vLLM path:04_MLOPS_AND_PRODUCTION_AI/LLM_Inference.

Pillar 01 — Highlights

01_AI_FUNDAMENTALS_AND_THEORY/
├── Mathematics_for_ML/                  NEW — linear algebra, calculus, probability, stats, convex opt
├── Statistical_Learning/                 NEW — regression, GLMs, time series, survival, A/B testing
├── Probabilistic_ML/                     NEW — PGMs, Gaussian processes, VI, MCMC, HMMs, PPLs
├── Classical_ML_Algorithms/              NEW — SVM, trees, RF, boosting, kNN, clustering, PCA
├── AutoML/                               NEW — HPO, AutoML frameworks, auto feature engineering
├── Feature_Engineering/                  NEW — selection, scaling/encoding, techniques
├── Model_Evaluation/                     NEW — metrics, model selection & validation
├── Machine_Learning/                    Classical ML, supervised/unsupervised
├── Deep_Learning/                       Architectures, regularization, optim
├── Reinforcement_Learning/
├── Generative_Models/                   GANs, VAEs, Diffusion, Flow, EBM
├── Computer_Vision/                     Self-supervised, ViT
├── Natural_Language_Processing/
├── Multimodal/
├── Graph_Neural_Networks/
├── Vision_Transformers/
├── Vision_Language_Models/
├── Video_Understanding/
├── LLM_Architectures/
├── Long_Context_Models/
├── State_Space_Models/                  NEW — Mamba, S4, RWKV, Hyena
├── Transfer_Learning, Federated_Learning, Few_Shot_Learning,
│   Meta_Learning, Contrastive_Learning, Domain_Adaptation,
│   Online_Learning, Active_Learning
├── Optimization_Algorithms/, Model_Optimization/
├── Explainable_AI/
├── Privacy_and_Security/
├── Quantum_Machine_Learning/
├── Prompt_Engineering/                  Use-case prompt libraries
├── Modern_Fine_Tuning/                  NEW — SFT, DPO, GRPO, LoRA, QLoRA
├── AI_Safety_and_Alignment/             NEW — RLHF, Constitutional AI, interp
├── Agentic_AI/                          NEW — ReAct, Reflexion, MCP, frameworks
├── RAG_and_Retrieval/                   NEW — RAG patterns, retrievers, rerank
├── AI_Evaluation/                       NEW — benchmarks, eval frameworks
├── Causal_Inference/                    NEW — DoWhy, EconML, frameworks
├── Courses/ Universities/ Communities/ Collections/

Pillar 02 — Highlights

02_LLM_AND_AI_MODELS/
├── Text_LLMs/
│   ├── Frontier_Closed_Models/          GPT-5, Claude 4.5, Gemini 2.5
│   ├── Open_Source_LLMs/                Llama, Qwen, Mistral, DeepSeek, GLM
│   ├── Reasoning_Models/                R1, Open-R1, Sky-T1
│   ├── Small_LLMs/                      Phi, Gemma, SmolLM
│   ├── Code_LLMs/, Specialized_LLMs/
│   ├── Efficient_Transformers/
├── Vision_Models/                       Detection, segmentation, image gen
├── Audio_Models/                        ASR, TTS, music
├── Video_Models/                        Text-to-video, image-to-video
├── Multimodal_Models/                   VLMs, GLM-V, Qwen-VL
├── Scientific_Models/                   Protein, Quantum ML, Reservoir
├── Time_Series_Models/
├── MoE_Models/                          NEW — Mixtral, DeepSeek, OLMoE
├── Diffusion_Models/                    NEW — SD3.5, FLUX, Veo, Wan, Sora
├── World_Models/                        NEW — Genie, Cosmos, V-JEPA, GR00T
├── Foundation_Models/, Frameworks/
├── Papers/, Research_Labs/, Communities/
└── Guides_and_Tutorials/, Collections/

Pillar 03 — Highlights

03_DATASETS_TOOLS_AND_RESOURCES/
├── Datasets/
│   ├── Computer_Vision_Datasets/
│   ├── NLP_Datasets/
│   ├── Audio_Datasets/, Video_Datasets/
│   ├── Multimodal_Datasets/             VQA, autonomous driving
│   ├── Time_Series_Datasets/, Tabular_Datasets/
│   ├── Climate_and_Geospatial/          Earth observation, oceanography
│   ├── Bioinformatics_and_Genomics/
│   ├── Finance_Datasets/, Gaming_and_RL/
│   ├── Robotics_Datasets/, Social_Science_Datasets/
│   ├── Open_Data_Portals/
│   ├── Synthetic_Data/, Web_Datasets/
│   └── Famous_Benchmarks/
├── Data_Engineering/                    Pipelines, versioning, quality,
│                                        annotation, feature engineering,
│                                        feature stores, ETL, web scraping
├── Storage_and_Databases/               Vector, time-series, document,
│                                        in-memory, lakes, warehouses
└── Cloud_Platforms/                     AWS / others

Pillar 04 — Highlights

04_MLOPS_AND_PRODUCTION_AI/
├── MLOps_Platforms/                     MLflow, Kubeflow, ZenML, Metaflow
├── Model_Serving/                       Triton, BentoML, KServe, Ray Serve
├── LLM_Inference/                       NEW — vLLM, SGLang, TensorRT-LLM,
│                                        TGI, llama.cpp, Ollama, MLX, MLC
├── Inference_Optimization/              ONNX, TensorRT, quantization
├── Model_Optimization/, Model_Registry_Solutions/
├── Workflow_Orchestration/              Airflow, Prefect, Dagster
├── Deployment/                          Kubernetes, Docker, Serverless
├── AB_Testing_and_Canary/
├── AI_Observability/                    NEW — Langfuse, LangSmith, Weave,
│                                        Phoenix, Helicone, Arize, OpenLLMetry
├── AI_Agents/                           Production agent stacks
├── Cloud_Platforms/                     Azure/Microsoft, others
└── API_Integration_Tools/

Pillar 05 — Highlights

05_VERTICAL_APPLICATIONS/
├── 01_Healthcare_and_Medical_AI/        Imaging, clinical NLP, drug discovery,
│                                        radiology, cardiology, neurology,
│                                        genomics, telemedicine, mental health
├── 02_Finance_and_Fintech_AI/           Banking (KYC/AML/fraud) + Financial Markets (stocks, options, FX, crypto, quant), credit, risk
├── 03_Agriculture_AgTech/               Precision farming, biomass, vegetation
├── 04_Climate_and_Sustainability/       Weather, Earth obs
├── 05_Education_AI/
├── 06_Legal_AI/
├── 07_Retail_and_Ecommerce/
├── 08_Manufacturing_and_Industry_AI/    NEW — PdM, QC, digital twins
├── 09_Entertainment_and_Creative_AI/
├── 10_Robotics_and_Embodied_AI/         VLAs, manipulation, humanoids
├── 11_Autonomous_Vehicles_AI/           NEW — UniAD, GAIA, datasets, sims
├── 12_Business_and_Marketing_AI/
├── 13_Energy_AI/                        NEW — Grid, renewables, fusion
├── 14_Cybersecurity_AI/                 NEW — Red/Blue team, model security
├── 15_Science_AI/
├── 16_Edge_and_IoT_AI/
├── 17_Conversational_AI/
├── 18_Predictive_AI/
├── 19_Computer_Vision_Applications/
└── 20_AI_Project_Showcases/             AutoML, Kaggle, RL, NLP, multimodal

💬 Community (Reddit & Discord)

Share an AIForge link on Reddit or Discord and it renders a rich preview (title, description, image, accent color) automatically — the repo ships complete Open Graph + theme-color tags tuned for both.

Curated community lists:

Reddit: AI/ML subreddits — r/MachineLearning, r/LocalLLaMA, r/StableDiffusion, r/PromptEngineering, and more.
Discord: AI/ML servers — Hugging Face (224k+), EleutherAI, LAION, MLOps Community, and more.

💬 Official community — MACHINE LEARNING KNBIS on Discord — join for AI/ML discussion, LLMs, MLOps, papers, and AIForge updates.

Share AIForge: Tweet · LinkedIn · Reddit · Hacker News

See the full growth plan in DISCOVERABILITY.md.

❓ Frequently Asked Questions (FAQ)

What is AIForge? AIForge is a free, open-source, curated index of the entire Artificial Intelligence, Machine Learning, Deep Learning, LLM, and Data Science ecosystem — 2,200+ curated documents linking to 7,500+ external resources, organized into a clean, duplicate-free, English-only taxonomy of 5 pillars plus a Frontier AI 2026 radar. Every directory has an index README, and a complete sitemap (2,700+ URLs) covers every folder and file.

Who is AIForge for? Data scientists, ML/AI engineers, researchers, students, and anyone who wants a single, well-organized map of AI/ML resources — from theory to production.

How is AIForge organized? Five pillars: (01) Fundamentals & Theory, (02) LLM & AI Models, (03) Datasets/Tools/Resources, (04) MLOps & Production AI, (05) Vertical Applications — plus (00) Frontier AI 2026 for the newest releases. Browse INDEX.md (full sitemap) or NAVIGATION_GUIDE.md (topic-first lookup).

Where do I find the latest AI models (GPT-5.5, Claude, DeepSeek, Llama 4)? See 00_FRONTIER_AI_2026.

Where are Kaggle winning solutions? See 05_VERTICAL_APPLICATIONS/20_AI_Project_Showcases/Kaggle — 216-competition index, top public notebooks, and curated winning write-ups.

Where do I find datasets, vector databases, or the HuggingFace ecosystem? See 03_DATASETS_TOOLS_AND_RESOURCES, including HuggingFace_Hub and Research_Platforms_and_Preprints.

How do I deploy/serve LLMs (vLLM, SGLang, llama.cpp)? See 04_MLOPS_AND_PRODUCTION_AI/LLM_Inference.

Is AIForge readable by AI assistants? Yes — it ships an llms.txt following the llmstxt.org convention so LLMs, AI agents, and AI search engines can discover, navigate, and cite the right section.

What language is AIForge in? 100% English — every page, heading, filename, and directory path. This keeps the taxonomy consistent and maximizes discoverability for global search engines and AI assistants.

How can I contribute? See CONTRIBUTING.md.

🏷️ Topics & Keywords

artificial-intelligence · machine-learning · deep-learning · large-language-models · llm · generative-ai · data-science · mlops · datasets · awesome-list · awesome · computer-vision · nlp · natural-language-processing · reinforcement-learning · transformers · diffusion-models · rag · ai-agents · huggingface · kaggle · pytorch · tensorflow · model-deployment · vector-database · ai-resources · curated-list

Searching for "awesome machine learning list", "AI resources collection", "deep learning index", "LLM resources", "MLOps tools list", "Kaggle winning solutions", "AI datasets directory", or "machine learning roadmap"? You're in the right place.

Contributing

See CONTRIBUTING.md. New resources should go to the canonical English snake_case directory; if no fit exists, propose a new one in your PR.

Code of Conduct & Security

License

MIT — see LICENSE.

artificial-intelligence

awesome

awesome-list

computer-vision

data-science

datasets

deep-learning

frameworks

generative-ai

llm

machine-learning

mlops

models

nlp

python

pytorch

research

tensorflow

Contributors

FELIPEACASTRO

175 commits

claude

56 commits

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FELIPEACASTRO/AIForge

Jupyter Notebook

231 commits

updated Aug 15, 2026

See the code

README

AIForge — The Definitive Repository for AI, ML, and Data Science

2,200+ documents · 100% English · every directory carries an index README with keywords · a complete sitemap.xml (2,700+ URLs) covers every folder and file — built for maximum search-engine and LLM discoverability.

🚀 Start Here: Frontier AI 2026

Five Pillars

#	Pillar	What lives here
01	AI Fundamentals & Theory	Foundational ML/DL theory, algorithms, paradigms (RL, GenAI, Transformers, SSMs), training methods, safety, evaluation.
02	LLM & AI Models	Frontier LLMs, open-source models, vision/audio/video/multimodal models, MoE, diffusion, world models, frameworks.
03	Datasets, Tools & Resources	Curated datasets by modality, data engineering, storage & databases, cloud, global AI ecosystem coverage, HuggingFace Hub, research/preprint platforms.
04	MLOps & Production AI	Model serving, LLM inference (vLLM/SGLang/TensorRT-LLM/llama.cpp), MLOps platforms, observability, deployment.
05	Vertical Applications	Industry-specific AI + Kaggle competitions & winning solutions: Healthcare, Banking (KYC/onboarding, AML, fraud), Financial Markets (stocks, options, futures, bonds, FX, crypto, quant trading), Agriculture, Robotics, AV, more.

How to Navigate

Browse by pillar. Each pillar has a sub-tree of canonical, English, snake_case topics — no duplicates, no language drift.

Use INDEX.md. The complete sitemap with every category and a one-line description.

Use NAVIGATION_GUIDE.md. A topic-first guide ("I want to learn about RAG" → exact path).

GitHub search. Scoped path search: vLLM path:04_MLOPS_AND_PRODUCTION_AI/LLM_Inference.

Pillar 01 — Highlights

01_AI_FUNDAMENTALS_AND_THEORY/
├── Mathematics_for_ML/                  NEW — linear algebra, calculus, probability, stats, convex opt
├── Statistical_Learning/                 NEW — regression, GLMs, time series, survival, A/B testing
├── Probabilistic_ML/                     NEW — PGMs, Gaussian processes, VI, MCMC, HMMs, PPLs
├── Classical_ML_Algorithms/              NEW — SVM, trees, RF, boosting, kNN, clustering, PCA
├── AutoML/                               NEW — HPO, AutoML frameworks, auto feature engineering
├── Feature_Engineering/                  NEW — selection, scaling/encoding, techniques
├── Model_Evaluation/                     NEW — metrics, model selection & validation
├── Machine_Learning/                    Classical ML, supervised/unsupervised
├── Deep_Learning/                       Architectures, regularization, optim
├── Reinforcement_Learning/
├── Generative_Models/                   GANs, VAEs, Diffusion, Flow, EBM
├── Computer_Vision/                     Self-supervised, ViT
├── Natural_Language_Processing/
├── Multimodal/
├── Graph_Neural_Networks/
├── Vision_Transformers/
├── Vision_Language_Models/
├── Video_Understanding/
├── LLM_Architectures/
├── Long_Context_Models/
├── State_Space_Models/                  NEW — Mamba, S4, RWKV, Hyena
├── Transfer_Learning, Federated_Learning, Few_Shot_Learning,
│   Meta_Learning, Contrastive_Learning, Domain_Adaptation,
│   Online_Learning, Active_Learning
├── Optimization_Algorithms/, Model_Optimization/
├── Explainable_AI/
├── Privacy_and_Security/
├── Quantum_Machine_Learning/
├── Prompt_Engineering/                  Use-case prompt libraries
├── Modern_Fine_Tuning/                  NEW — SFT, DPO, GRPO, LoRA, QLoRA
├── AI_Safety_and_Alignment/             NEW — RLHF, Constitutional AI, interp
├── Agentic_AI/                          NEW — ReAct, Reflexion, MCP, frameworks
├── RAG_and_Retrieval/                   NEW — RAG patterns, retrievers, rerank
├── AI_Evaluation/                       NEW — benchmarks, eval frameworks
├── Causal_Inference/                    NEW — DoWhy, EconML, frameworks
├── Courses/ Universities/ Communities/ Collections/

Pillar 02 — Highlights

02_LLM_AND_AI_MODELS/
├── Text_LLMs/
│   ├── Frontier_Closed_Models/          GPT-5, Claude 4.5, Gemini 2.5
│   ├── Open_Source_LLMs/                Llama, Qwen, Mistral, DeepSeek, GLM
│   ├── Reasoning_Models/                R1, Open-R1, Sky-T1
│   ├── Small_LLMs/                      Phi, Gemma, SmolLM
│   ├── Code_LLMs/, Specialized_LLMs/
│   ├── Efficient_Transformers/
├── Vision_Models/                       Detection, segmentation, image gen
├── Audio_Models/                        ASR, TTS, music
├── Video_Models/                        Text-to-video, image-to-video
├── Multimodal_Models/                   VLMs, GLM-V, Qwen-VL
├── Scientific_Models/                   Protein, Quantum ML, Reservoir
├── Time_Series_Models/
├── MoE_Models/                          NEW — Mixtral, DeepSeek, OLMoE
├── Diffusion_Models/                    NEW — SD3.5, FLUX, Veo, Wan, Sora
├── World_Models/                        NEW — Genie, Cosmos, V-JEPA, GR00T
├── Foundation_Models/, Frameworks/
├── Papers/, Research_Labs/, Communities/
└── Guides_and_Tutorials/, Collections/

Pillar 03 — Highlights

03_DATASETS_TOOLS_AND_RESOURCES/
├── Datasets/
│   ├── Computer_Vision_Datasets/
│   ├── NLP_Datasets/
│   ├── Audio_Datasets/, Video_Datasets/
│   ├── Multimodal_Datasets/             VQA, autonomous driving
│   ├── Time_Series_Datasets/, Tabular_Datasets/
│   ├── Climate_and_Geospatial/          Earth observation, oceanography
│   ├── Bioinformatics_and_Genomics/
│   ├── Finance_Datasets/, Gaming_and_RL/
│   ├── Robotics_Datasets/, Social_Science_Datasets/
│   ├── Open_Data_Portals/
│   ├── Synthetic_Data/, Web_Datasets/
│   └── Famous_Benchmarks/
├── Data_Engineering/                    Pipelines, versioning, quality,
│                                        annotation, feature engineering,
│                                        feature stores, ETL, web scraping
├── Storage_and_Databases/               Vector, time-series, document,
│                                        in-memory, lakes, warehouses
└── Cloud_Platforms/                     AWS / others

Pillar 04 — Highlights

04_MLOPS_AND_PRODUCTION_AI/
├── MLOps_Platforms/                     MLflow, Kubeflow, ZenML, Metaflow
├── Model_Serving/                       Triton, BentoML, KServe, Ray Serve
├── LLM_Inference/                       NEW — vLLM, SGLang, TensorRT-LLM,
│                                        TGI, llama.cpp, Ollama, MLX, MLC
├── Inference_Optimization/              ONNX, TensorRT, quantization
├── Model_Optimization/, Model_Registry_Solutions/
├── Workflow_Orchestration/              Airflow, Prefect, Dagster
├── Deployment/                          Kubernetes, Docker, Serverless
├── AB_Testing_and_Canary/
├── AI_Observability/                    NEW — Langfuse, LangSmith, Weave,
│                                        Phoenix, Helicone, Arize, OpenLLMetry
├── AI_Agents/                           Production agent stacks
├── Cloud_Platforms/                     Azure/Microsoft, others
└── API_Integration_Tools/

Pillar 05 — Highlights

05_VERTICAL_APPLICATIONS/
├── 01_Healthcare_and_Medical_AI/        Imaging, clinical NLP, drug discovery,
│                                        radiology, cardiology, neurology,
│                                        genomics, telemedicine, mental health
├── 02_Finance_and_Fintech_AI/           Banking (KYC/AML/fraud) + Financial Markets (stocks, options, FX, crypto, quant), credit, risk
├── 03_Agriculture_AgTech/               Precision farming, biomass, vegetation
├── 04_Climate_and_Sustainability/       Weather, Earth obs
├── 05_Education_AI/
├── 06_Legal_AI/
├── 07_Retail_and_Ecommerce/
├── 08_Manufacturing_and_Industry_AI/    NEW — PdM, QC, digital twins
├── 09_Entertainment_and_Creative_AI/
├── 10_Robotics_and_Embodied_AI/         VLAs, manipulation, humanoids
├── 11_Autonomous_Vehicles_AI/           NEW — UniAD, GAIA, datasets, sims
├── 12_Business_and_Marketing_AI/
├── 13_Energy_AI/                        NEW — Grid, renewables, fusion
├── 14_Cybersecurity_AI/                 NEW — Red/Blue team, model security
├── 15_Science_AI/
├── 16_Edge_and_IoT_AI/
├── 17_Conversational_AI/
├── 18_Predictive_AI/
├── 19_Computer_Vision_Applications/
└── 20_AI_Project_Showcases/             AutoML, Kaggle, RL, NLP, multimodal

💬 Community (Reddit & Discord)

Curated community lists:

Reddit: AI/ML subreddits — r/MachineLearning, r/LocalLLaMA, r/StableDiffusion, r/PromptEngineering, and more.
Discord: AI/ML servers — Hugging Face (224k+), EleutherAI, LAION, MLOps Community, and more.

💬 Official community — MACHINE LEARNING KNBIS on Discord — join for AI/ML discussion, LLMs, MLOps, papers, and AIForge updates.

Share AIForge: Tweet · LinkedIn · Reddit · Hacker News

See the full growth plan in DISCOVERABILITY.md.

❓ Frequently Asked Questions (FAQ)

Who is AIForge for? Data scientists, ML/AI engineers, researchers, students, and anyone who wants a single, well-organized map of AI/ML resources — from theory to production.

Where do I find the latest AI models (GPT-5.5, Claude, DeepSeek, Llama 4)? See 00_FRONTIER_AI_2026.

Where are Kaggle winning solutions? See 05_VERTICAL_APPLICATIONS/20_AI_Project_Showcases/Kaggle — 216-competition index, top public notebooks, and curated winning write-ups.

Where do I find datasets, vector databases, or the HuggingFace ecosystem? See 03_DATASETS_TOOLS_AND_RESOURCES, including HuggingFace_Hub and Research_Platforms_and_Preprints.

How do I deploy/serve LLMs (vLLM, SGLang, llama.cpp)? See 04_MLOPS_AND_PRODUCTION_AI/LLM_Inference.

How can I contribute? See CONTRIBUTING.md.

🏷️ Topics & Keywords

Searching for "awesome machine learning list", "AI resources collection", "deep learning index", "LLM resources", "MLOps tools list", "Kaggle winning solutions", "AI datasets directory", or "machine learning roadmap"? You're in the right place.

Contributing

See CONTRIBUTING.md. New resources should go to the canonical English snake_case directory; if no fit exists, propose a new one in your PR.

Code of Conduct & Security

License

MIT — see LICENSE.

artificial-intelligence

awesome

awesome-list

computer-vision

data-science

datasets

deep-learning

frameworks

generative-ai

llm

machine-learning

mlops

models

nlp

python

pytorch

research

tensorflow

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Learn AI and LLMs from scratch using free resources

6,063

filipecalegario/awesome-generative-ai

A curated list of Generative AI tools, works, models, and references

3,541

Contributors

FELIPEACASTRO

175 commits

claude

56 commits

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Jupyter Notebook

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