Introduction to Matplotlib

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Explores neural networks, activation functions, backpropagation, and PyTorch implementation.

Introduces NumPy, focusing on array creation, manipulation, and its advantages for scientific computing.

Introduces Mathematica basics, including graphics creation, list manipulation, and function definition.

Covers the definition of applications, image of elements, and direct and reciprocal images.

Covers Python basics, Pandas, data manipulation, visualization, and machine learning.

Covers functions, including even and odd functions, periodicity, and function operations.

Provides a Python crash course covering basic arithmetics, complex numbers, strings, lists, dictionaries, and more.

Introduces the fundamentals of functions in microcontroller programming, emphasizing naming rules and step-by-step development.

Covers advanced Python topics like numpy operations, scipy linear algebra, and matplotlib for creating figures.

Explores differentiating under the integral sign and continuity of functions in integrals.