Awesome AI for developers: knowledge sharing and AI cheat sheets.
See the codeREADME
Knowledge sharing - Cheat sheets (AI)
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.
- The KS cheat sheet (AI) can be found at the following URL: https://ai-helpers.github.io/kscs-website/
Table of Contents (ToC)
Overview
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.
Quick Links
Sections
API
| Subsection | Description | Link |
|---|---|---|
| FastAPI | Fast Python web framework for RESTful APIs | FastAPI |
| Ray | Distributed computing framework for ML workloads | Ray |
BI
| Subsection | Description | Link |
|---|---|---|
| BI as Code | Open source examples for Business Intelligence | BI |
Clouds
| 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 |
Generative AI
| 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 |
Git
| Subsection | Description | Link |
|---|---|---|
| Git | Version control and collaboration | Git |
MLOps
| Subsection | Description | Link |
|---|---|---|
| ZenML | MLOps framework | ZenML |
Predictive AI
| 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 |
Python
| Subsection | Description | Link |
|---|---|---|
| Poetry | Dependency management | Poetry |
| pyenv | Python version management | pyenv |
| UV | Fast package installer | UV |
Rust
| Subsection | Description | Link |
|---|---|---|
| Rust | System programming language | Rust |
Trustworthy AI
| Subsection | Description | Link |
|---|---|---|
| AI Risk | Risk assessment frameworks | AI Risk |
| Principles | Ethical AI guidelines | Principles |
| Strategy | Trust and governance practices | Strategy |
Frontend
| Subsection | Description | Link |
|---|---|---|
| Streamlit | Data app framework | Streamlit |
| Django | Web framework | Django |
| Tailwind CSS | Utility-first CSS framework | Tailwind CSS |
Related repository
Others
Data
References:
- Medium - Synthetic data tools
- Github - Awesome synthetic data (statice)
- Github - Awesome synthetic data (gretelai)
Opendata
Contributors
280 commits
Similar repos
Languages
Jupyter Notebook
98.3%
Python
1.7%
Awesome AI for developers: knowledge sharing and AI cheat sheets.
See the codeREADME
Knowledge sharing - Cheat sheets (AI)
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.
- The KS cheat sheet (AI) can be found at the following URL: https://ai-helpers.github.io/kscs-website/
Table of Contents (ToC)
Overview
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.
Quick Links
Sections
API
| Subsection | Description | Link |
|---|---|---|
| FastAPI | Fast Python web framework for RESTful APIs | FastAPI |
| Ray | Distributed computing framework for ML workloads | Ray |
BI
| Subsection | Description | Link |
|---|---|---|
| BI as Code | Open source examples for Business Intelligence | BI |
Clouds
| 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 |
Generative AI
| 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 |
Git
| Subsection | Description | Link |
|---|---|---|
| Git | Version control and collaboration | Git |
MLOps
| Subsection | Description | Link |
|---|---|---|
| ZenML | MLOps framework | ZenML |
Predictive AI
| 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 |
Python
| Subsection | Description | Link |
|---|---|---|
| Poetry | Dependency management | Poetry |
| pyenv | Python version management | pyenv |
| UV | Fast package installer | UV |
Rust
| Subsection | Description | Link |
|---|---|---|
| Rust | System programming language | Rust |
Trustworthy AI
| Subsection | Description | Link |
|---|---|---|
| AI Risk | Risk assessment frameworks | AI Risk |
| Principles | Ethical AI guidelines | Principles |
| Strategy | Trust and governance practices | Strategy |
Frontend
| Subsection | Description | Link |
|---|---|---|
| Streamlit | Data app framework | Streamlit |
| Django | Web framework | Django |
| Tailwind CSS | Utility-first CSS framework | Tailwind CSS |
Related repository
Others
Data
References:
- Medium - Synthetic data tools
- Github - Awesome synthetic data (statice)
- Github - Awesome synthetic data (gretelai)
Opendata
Similar repos
Contributors
280 commits
Languages
Jupyter Notebook
98.3%
Python
1.7%