--- id: "/data-datasets/advanced/page/2/" title: "Data & datasets for advanced learners · page 2" url: "https://skillissue.dev/data-datasets/advanced/page/2/" --- # Data & datasets for advanced learners [Beginner](/data-datasets/beginner/index.md) [Intermediate](/data-datasets/intermediate/index.md) [Advanced](/data-datasets/advanced/index.md) [Expert](/data-datasets/expert/index.md) 45 resources · page 2 of 2 - ### [Ai2 model cards and datasets](/context-engineering/retrieval-and-rag/ai2-model-cards-and-datasets/index.md) by [Ai2](https://huggingface.co/allenai) Ai2's Hugging Face organisation page listing its model checkpoints, model cards and datasets, including OLMo. Advanced learning_resource docs US en - ### [Alibi Detect](/context-engineering/retrieval-and-rag/alibi-detect/index.md) by [Seldon](https://www.seldon.io/) Alibi Detect documentation: Python library for outlier, adversarial and data-drift detection in ML systems. Advanced learning_resource docs UK/global en - ### [Cleanlab documentation](/context-engineering/retrieval-and-rag/cleanlab-documentation/index.md) by [Cleanlab](https://cleanlab.ai/) Cleanlab documentation: open-source library for finding label errors and data issues in ML datasets. Advanced learning_resource docs US en - ### [Datasheets for Datasets](/context-engineering/retrieval-and-rag/datasheets-for-datasets/index.md) by [Timnit Gebru et al. (Microsoft Research)](https://www.microsoft.com/en-us/research/) Microsoft Research page for Datasheets for Datasets, proposing standard documentation for ML datasets. Advanced learning_resource paper United States / international collaboration en - ### [LanceDB documentation](/context-engineering/retrieval-and-rag/lancedb-documentation/index.md) by [LanceDB](https://lancedb.com/) LanceDB documentation: multimodal lakehouse and vector database for AI data, with versioned tables and retrieval. Advanced learning_resource docs US en - ### [LLM-jp corpora (GitLab)](/context-engineering/retrieval-and-rag/llm-jp-corpora-gitlab/index.md) by [LLM-jp (National Institute of Informatics)](https://llm-jp.nii.ac.jp/) LLM-jp datasets on the NII GitLab: open Japanese pretraining corpora. Advanced learning_resource docs Japan ja - ### [NeurIPS paper checklist](/context-engineering/retrieval-and-rag/neurips-paper-checklist/index.md) by [NeurIPS Foundation](https://neurips.cc/) NeurIPS paper checklist covering assumptions, limitations, experimental details, reproducibility and broader impacts. Advanced learning_resource guide Global en - ### [Qdrant documentation](/context-engineering/retrieval-and-rag/qdrant-documentation/index.md) by [Qdrant](https://qdrant.tech/) Qdrant documentation: vector search engine with quickstarts, filtering, hybrid search and deployment guides. Advanced learning_resource docs Germany en - ### [Retrieval-Augmented Generation](/context-engineering/retrieval-and-rag/retrieval-augmented-generation/index.md) by [Patrick Lewis et al. (Facebook AI Research)](https://ai.meta.com/) arXiv paper (2020) "Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks", introducing retrieval-augmented generation (RAG). Advanced learning_resource paper US; UK en - ### [RL environments for LLM agents: Design, rewards, and validation (Snorkel)](/context-engineering/retrieval-and-rag/snorkel-rl-environments-for-llm-agents-design-rewards-validation/index.md) by [Snorkel AI](https://snorkel.ai/) Snorkel AI post on designing RL environments for LLM agents: state, actions, rewards and validation. Advanced learning_resource blog US en - ### [Partial Credit in RL: When It Opposes Completion (Snorkel)](/context-engineering/retrieval-and-rag/snorkel-when-partial-credit-opposes-completion/index.md) by [Snorkel AI](https://snorkel.ai/) Snorkel AI post on how partial-credit rewards in reinforcement learning can work against task completion. Advanced learning_resource blog US en - ### [Training Compute-Optimal Large Language Models](/context-engineering/retrieval-and-rag/training-compute-optimal-large-language-models/index.md) by [Jordan Hoffmann et al. (DeepMind)](https://deepmind.google/) arXiv paper (2022) "Training Compute-Optimal Large Language Models", describing Chinchilla and compute-optimal model size versus training tokens. Advanced learning_resource paper UK en - ### [Weaviate documentation](/context-engineering/retrieval-and-rag/weaviate-documentation/index.md) by [Weaviate](https://weaviate.io/) Weaviate documentation: open-source vector database with guides on indexing, search and RAG pipelines. Advanced learning_resource docs Netherlands en [Previous page](/data-datasets/advanced/index.md) [Plain-text Markdown copy](/data-datasets/advanced/page/2/index.md)