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Anaconda vs Dask: What are the differences?
Anaconda: The Enterprise Data Science Platform for Data Scientists, IT Professionals and Business Leaders. A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda; Dask: A flexible library for parallel computing in Python. It is a versatile tool that supports a variety of workloads. It is composed of two parts: Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads Big Data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of dynamic task schedulers. .
Anaconda and Dask can be categorized as "Data Science" tools.