Key Python Libraries:

• Django: A high-level Python web framework for rapid development of secure and scalable web applications.
• NumPy: The fundamental package for scientific computing with Python, providing support for large, multi-dimensional arrays and matrices, along with a collection of mathematical functions to operate on these arrays.
• Pandas: A powerful and easy-to-use open-source data analysis and manipulation library built on top of NumPy, providing data structures and functions for working with structured data.
• Matplotlib: A comprehensive library for creating static, animated, and interactive visualizations in Python, used for plotting various types of graphs, charts, and histograms.
• TensorFlow: An open-source machine learning framework developed by Google for building and training deep learning models, including neural networks, convolutional neural networks (CNNs), and recurrent neural networks (RNNs).
• Keras: A high-level neural networks API written in Python that works as an interface for TensorFlow, providing a user-friendly approach for building and experimenting with deep learning models.
• Scikit-learn: A simple and efficient tool for data mining and data analysis, providing a range of supervised and unsupervised learning algorithms for classification, regression, clustering, dimensionality reduction, and more.