awesome-aiml-blog
github.com/youngmki/awesome-aiml-blog ↗These are excerpts from various blog posts related to AI & ML that deal with important research and business cases.
21
GitHub Stars
121
Curated Resources
3
Categories
1 hour ago
Last Refreshed
1. Research2. Business Cases and Implementations3. AWS ML Only
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me 2.3. recsys, etc. resources from awesome-aiml-blog"
Installation instructions →What's inside
2. Business Cases and Implementations
3. AWS ML Only
- 컨테이너 패키지3.4. Training, Inference and MLOps
- Amazon SageMaker Automatic Model Tuning Now Supports Three New Completion Criteria for HPO (Feb 2023)3.4. Training, Inference and MLOps
- Amazon SageMaker Built-In LightGBM Now Offers Distributed Training Using Dask (Jan 2023)3.3 RecSys, etc.
- 농심의 Amazon SageMaker를 활용한 원자재 가격예측과 MLOps 여정 (Feb 2023)3.4. Training, Inference and MLOps
- AWS를 이용한 MLOps 구축 사례 살펴보기 (Jan 2023)3.4. Training, Inference and MLOps
- Best Practices for Amazon SageMaker Training Managed Warm Pools (Dec 2022)3.4. Training, Inference and MLOps
1. Research
- Accelerating Text Generation with Confident Adaptive Language Modeling (CALM) (Dec 2022, Google)1.2. NLP
- Aligning LMs to Follow Instructions (Jan 2022, OpenAI)1.2. NLP
- Atlas: Few-Shot Learning with Retrieval Augmented LMs (Jan 2023, Meta)1.2. NLP
- Autoencoders and Diffusers: A Brief Comparison (Dec 2022)1.1. CV
- Better LMs without Massive Compute (Nov 2022, Google)1.2. NLP
- Building on Top of Black Magic (Oct 2022)1.3. RecSys, etc.
Showing a sample of 121 resources. View the full list on GitHub →