Prominent Python Libraries for Data Science

Data Science Libraries


Introduction

Body

Due to its rich repository of data science libraries. Python has emerged as the preferred language for analytics and data science. The prominent libraries are -

NumPy: It is a basic numerical package which provides tools to perform operations on N-dimensional arrays and matrices.

Pandas: Crucial for data analysis processes, it offers data manipulation structures such as DataFrames facilitating the organization and analysis of structured information.

Matplotlib: a plotting library for graphing the data, particularly useful in the making of static, animated, or interactive plots.

Scikit-learn: A machine learning framework that implements a number of algorithms suitable for various tasks including classification, regression, and clustering.

TensorFlow: A reliable toolkit for neural networks and artificial intelligence deep learning applications.

Conclusion

These libraries drive data science applications and assist in a number of activities including data preprocessing, model building, and deployment.

References- DataCamp, GfG

Picture Credit- Makemeanalyst

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