15 open source tools that every data scientist should learn

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A versatile and widely used programming language with a vast ecosystem of data science libraries.

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A powerful language for statistical computing and graphics.

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A standard language for querying and manipulating data in relational databases.

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A web application for creating and sharing documents that contain live code, equations, visualizations, and narrative text.

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A Python library for data manipulation and analysis.

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NumPy: A Python library for working with arrays.

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Matplotlib: A Python library for creating visualizations.

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A Python library for machine learning.

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A Python library for deep learning.

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A Python library for deep learning.

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A unified analytics engine for large-scale data processing.

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A distributed computing framework for processing large datasets.

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A platform for programmatically scheduling and monitoring workflows.

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A tool for transforming data in warehouses.

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A workflow orchestration tool for managing data pipelines.

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