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This is a lecture on how to use NumPy and practice its application in real-world scenarios.

This is a lecture that condenses the math content learned in middle and high school. You will learn the necessary mathematical knowledge and techniques for each item with a lot of practice.

This is the fifth lecture in the [인공지능을 위한 파이썬] series. It is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python grammar.

This is the second lecture in the [Python for AI] series. It's a lecture that provides practical exercises used in machine learning and deep learning, alongside Python grammar.

This is a lecture on data visualization using the Matplotlib library.

This is a course that offers extensive practice in Python's basic syntax. This is a course that provides practical exercises used in Machine Learning and Deep Learning, along with Python's syntax.

[Python for AI] This is the fourth lecture in the series. It is a lecture that covers Python grammar along with practical exercises used in machine learning and deep learning.

[Python for AI] Third lecture in the series. Learn how to debug Python code.

This is the first lecture in linear algebra, and it is a lecture that geometrically understands vectors and vector operations.

This is a course where you learn the basic calculus and PyTorch's Autograd functionality needed to get started with deep learning.

Learn virtual environment concepts and setup methods.

This is a course that intensively covers gradient descent, the most fundamental learning algorithm in deep learning.

Limits of functions, derivatives, differentiation, derivative formula, applications of differentiation