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When starting with AI programming with Python, several essential libraries form the backbone of most projects. NumPy is crucial for numerical computations, while Pandas simplifies data manipulation. Matplotlib and Seaborn help visualize data effectively. Scikit-learn is perfect for machine learning models, preprocessing, and evaluation. For deep learning, TensorFlow and PyTorch are industry favorites, offering powerful neural network capabilities. NLTK or spaCy can handle natural language processing tasks, and OpenCV supports computer vision projects. Mastering these libraries provides a solid foundation for building, training, and deploying AI models efficiently.
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Posted : 13/08/2025 2:21 pm