A collection of cheat sheets and concise documentation aimed at facilitating knowledge sharing on various AI-related tools, technologies, and methodologies. This repository is intended to provide quick references and practical guides for both newcomers and experienced practitioners in the AI field.
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This repository provides a structured and categorized collection of cheat sheets, offering rapid access to essential knowledge for developing, deploying, and managing AI systems.
It covers a wide array of topics, including APIs, cloud services, generative AI techniques, modeling libraries, and principles of trustworthy AI.
A curated list of references, including official documentation, blogs, and research papers, to support the content provided in the cheat sheets.
| 🔌 API | 📊 BI | ☁️ Clouds | 🤖 Generative AI | 🔄 Git |
|---|---|---|---|---|
| ⚙️ MLOps | 📈 Predictive AI | 🐍 Python | 🦀 Rust | ⚖️ Trustworthy AI |
| Subsection | Description | Link |
|---|---|---|
| FastAPI | Fast Python web framework for RESTful APIs | FastAPI |
| Ray | Distributed computing framework for ML workloads | Ray |
| Subsection | Description | Link |
|---|---|---|
| BI as Code | Open source examples for Business Intelligence | BI |
| Subsection | Description | Link |
|---|---|---|
| AWS | Amazon Web Services for AI projects | AWS |
| Azure | Microsoft Azure AI services | Azure |
| GCP | Google Cloud Platform AI capabilities | GCP |
| OVH | OVHcloud for AI workloads | OVH |
| Scaleway | Scaleway cloud services for AI | Scaleway |
| Subsection | Description | Link |
|---|---|---|
| Agents | AI agents and architectures | Agents |
| Evaluation | Model evaluation techniques | Evaluation |
| Post-training | Fine-tuning and RLHF | Post-training |
| Model Providers | Generative AI provider comparisons | Providers |
| Hallucinations | Mitigating model hallucinations | Hallucinations |
| Inference | Model inference optimization | Inference |
| RAG | Retrieval-Augmented Generation | RAG |
| Structured Outputs | Output formatting and control | Structured Outputs |
| Tools | AI development tools | Tools |
| Unified Interface | Multi-provider interfaces | Unified Interface |
| Subsection | Description | Link |
|---|---|---|
| Git | Version control and collaboration | Git |
| Subsection | Description | Link |
|---|---|---|
| ZenML | MLOps framework | ZenML |
| Subsection | Description | Link |
|---|---|---|
| scikit-learn | Machine learning library | sklearn |
| skrub | Data preparation library | skrub |
| skore | Best practices for scikit-learn | skore |
| skops | Model sharing and deployment | skops |
| Subsection | Description | Link |
|---|---|---|
| Poetry | Dependency management | Poetry |
| pyenv | Python version management | pyenv |
| UV | Fast package installer | UV |
| Subsection | Description | Link |
|---|---|---|
| Rust | System programming language | Rust |
| Subsection | Description | Link |
|---|---|---|
| AI Risk | Risk assessment frameworks | AI Risk |
| Principles | Ethical AI guidelines | Principles |
| Strategy | Trust and governance practices | Strategy |
| Subsection | Description | Link |
|---|---|---|
| Streamlit | Data app framework | Streamlit |
| Django | Web framework | Django |
| Tailwind CSS | Utility-first CSS framework | Tailwind CSS |
References