#other #analytics #api #artificial_intelligence #aws #cheatsheet #data_science #data_wrangling #database #deep_learning #linux #machine_learning #neural_network #online_course #python #r #reinforcement_learning #scikit_learn #sql #statistics #visualization

https://github.com/tirthajyoti/Data-science-best-resources

#java #data_analysis #data_science #data_wrangling #datacleaning #datacleansing #datajournalism #datamining #journalism #opendata #reconciliation #wikidata

https://github.com/OpenRefine/OpenRefine

#rust #ckan #cli #csv #data_engineering #data_wrangling #datapackage #excel #geocode #luau #opendata #parquet #polars #postgresql #snappy #sql #sqlite #tsv

https://github.com/jqnatividad/qsv

#python #ai #cv #data_analytics #data_wrangling #embeddings #llm #llm_eval #machine_learning #mlops #multimodal

DataChain is a powerful tool for managing and processing large amounts of data, especially useful for artificial intelligence tasks. It helps you organize unstructured data from various sources like cloud storage or local files into structured datasets. You can process this data efficiently using Python, without needing SQL or Spark, and even use local AI models or APIs to enrich your data. Key benefits include parallel processing, out-of-memory computing, and optimized vector searches, making it faster and more efficient. Additionally, DataChain integrates well with popular libraries like PyTorch and TensorFlow, allowing you to easily export data for further analysis or training models. This makes it easier to handle complex data tasks and improves your overall workflow.

https://github.com/iterative/datachain