pandas for data manipulation

pandas simplifies reading and writing data from sources like SQL, CSV, and Excel, allowing data scientists to load, clean, and preprocess data for analysis quickly .

NumPy for numerical operations

NumPy provides essential mathematical functions like trigonometry, statistics, and linear algebra, making it crucial for data manipulation and analysis.

Matplotlib for visualizations

Visualizing data is key to insights and communication. Matplotlib lets data scientists create line, scatter, bar plot, histogram, and more charts with minimal code.

scikit-learn for machine learning

scikit-learn's consistent API allows data scientists to train and evaluate machine learning models without being overwhelmed by complex implementation details.

TensorFlow for deep learning

Deep learning has transformed data science fields like computer vision, NLP, and reinforcement learning. TensorFlow and PyTorch simplify building and training deep neural networks.

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