Linking pages
- GitHub - zhimin-z/awesome-awesome-artificial-intelligence: A curated list of awesome curated lists of many topics closely related to artificial intelligence. https://github.com/zhimin-z/awesome-awesome-artificial-intelligence 15 comments
- GitHub - zhimin-z/awesome-awesome-machine-learning: A curated list of awesome curated lists of many topics closely related to machine learning. https://github.com/zhimin-z/awesome-awesome-machine-learning 0 comments
Linked pages
- GitHub - code-kern-ai/refinery: The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact. https://github.com/code-kern-ai/refinery 57 comments
- GitHub - treeverse/lakeFS: lakeFS - Data version control for your data lake | Git for data https://github.com/treeverse/lakeFS 55 comments
- GitHub - iterative/dvc: 🦉 Data Version Control | Git for Data & Models | ML Experiments Management https://github.com/iterative/dvc 46 comments
- GitHub - langfuse/langfuse: Open source observability and analytics for LLM applications https://github.com/langfuse/langfuse 35 comments
- GitHub - huggingface/transformers: 🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. https://github.com/huggingface/transformers 26 comments
- GitHub - Renumics/spotlight: Interactively explore unstructured datasets from your dataframe. https://github.com/Renumics/spotlight 25 comments
- GitHub - cleverhans-lab/cleverhans: An adversarial example library for constructing attacks, building defenses, and benchmarking both https://github.com/cleverhans-lab/cleverhans 23 comments
- GitHub - cleanlab/cleanlab: The standard data-centric AI package for data quality and machine learning with messy, real-world data and labels. https://github.com/cleanlab/cleanlab 21 comments
- GitHub - slundberg/shap: A game theoretic approach to explain the output of any machine learning model. https://github.com/slundberg/shap 20 comments
- GitHub - deepchecks/deepchecks: Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and models from research to production. https://github.com/deepchecks/deepchecks 17 comments
- GitHub - towhee-io/towhee: Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast. https://github.com/towhee-io/towhee 14 comments
- GitHub - sdv-dev/SDV: Synthetic data generation for tabular data https://github.com/sdv-dev/SDV 13 comments
- GitHub - marcotcr/lime: Lime: Explaining the predictions of any machine learning classifier https://github.com/marcotcr/lime 12 comments
- GitHub - Giskard-AI/giskard: 🐢 Open-Source Evaluation & Testing framework for LLMs and ML models https://github.com/Giskard-AI/giskard 8 comments
- GitHub - lightly-ai/lightly: A python library for self-supervised learning on images. https://github.com/lightly-ai/lightly 4 comments
- GitHub - Arize-ai/phoenix: AI Observability & Evaluation - Evaluate, troubleshoot, and fine tune your LLM, CV, and NLP models in a notebook. https://github.com/Arize-ai/phoenix 3 comments
- GitHub - voxel51/fiftyone: The open-source tool for building high-quality datasets and computer vision models https://github.com/voxel51/fiftyone 1 comment
- GitHub - evidentlyai/evidently: Evidently is an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics. https://github.com/evidentlyai/evidently 1 comment
- Data-Centric AI Community · GitHub https://github.com/Data-Centric-AI-Community 1 comment
- GitHub - ydataai/ydata-profiling: Create HTML profiling reports from pandas DataFrame objects https://github.com/ydataai/ydata-profiling 1 comment
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