1 dépôt
Awesome GitHub RepositoriesSingle-Sample Stream Iterators
Yields data samples one by one from files, databases, or live sources without loading everything into memory.
Distinct from Async Iterable Streams: Distinct from Async Iterable Streams: focuses on synchronous single-sample iteration for online ML, not async chunked processing.
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Awesome Single-Sample Stream Iterators GitHub Repositories
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- bitly/data_hacks
bitly/data_hacks
1,979Voir sur GitHubData Hacks is a collection of command-line utilities designed for statistical computation, real-time stream processing, and text-based data visualization. The toolkit enables users to perform rapid analysis on large datasets directly within the terminal by processing information through standard input and output streams. The project distinguishes itself through its focus on memory-efficient, stream-oriented operations that allow for the analysis of large-scale data without requiring heavy infrastructure. It utilizes stateless functional transformations and reservoir sampling to handle data st
Samples data streams by selecting random subsets of records to facilitate analysis of large datasets.
Python
