Python Libraries                Every Data Scientist                Should Know

10

1

NumPy

NumPy is a Python library that empowers data manipulation and analysis, serving as the cornerstone for other data science packages like Pandas and Matplotlib

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2

Pandas is a swift, flexible, & user-friendly data analysis and manipulation tool. It's indispensable for data cleaning, modeling, and analysis, making it a must-know library.

Pandas

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3

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Matplotlib

Matplotlib offers an array of functions for crafting static, animated, & interactive visualizations. In 2024, it remains pivotal for creating stunning charts, graphs, & data visualizations.

4

Data Science & Data Analytics

Data scientists can't go without Scikit-learn. It provides a multitude of machine learning algorithms and tools, making it ideal for building classification and regression models.

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5

TensorFlow

TensorFlow is a vital library for deep learning in 2024. It equips data scientists with the tools needed for tasks like image recognition and natural language processing.

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6

PyTorch is another essential library for deep learning tasks, such as image recognition and NLP. It's a top choice for data scientists due to its flexibility and performance.

PyTorch

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7

Keras

Keras, with its high-level API, simplifies building and training deep learning models. It's widely used for image recognition, NLP, and more, making it indispensable for data scientists.

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8

Theano

Theano offers a low-level API for deep learning model development. While it's a bit more specialized, it's still crucial for image recognition and NLP tasks in 2024.

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9

SciPy

SciPy is your go-to library for scientific computing. It boasts functions for statistical analysis, signal processing, & image processing, making it indispensable for data scientists.

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10

Seaborn

Seaborn, though not as famous as the others, is an essential library in 2024. It simplifies data visualization, especially for statistical plots and informative graphics.

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