인프런 - 라이프타임 커리어 플랫폼

This is a lecture where you can easily learn important mathematical concepts used in games. People who are well-versed in mathematics take this knowledge for granted, so they cannot teach it assuming you know nothing. I explain from a beginner's perspective, truly assuming you are a non-major.

This course covers introduction to linear algebra, and you can master introduction to linear algebra through the lectures.

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

Covers essential linear algebra for Machine Learning/Deep Learning research.

In this course, you will learn how to solve various matrix calculation related problems using Python's SciPy library. Even if you do not know Python or have only a little prior knowledge, you will be able to solve the given problems.

Master the linear algebra content required for AI/deep learning by investing 10 minutes a day and completing it in one month.

Were you a math-phobe during your school days? It's said that math is important in AI, but do you feel lost on how to approach it? The reason math is important in AI is because math is used in the computational processes of AI (Machine Learning and Deep Learning). For easy explanations of differentiation, linear algebra, and probability and statistics to understand AI, it is structured with simple explanations using graphs (coordinates) rather than mathematical derivations.

This is optimization theory required for AI/deep learning, computer vision, computer graphics, and more. Optimization Theory 1 focuses primarily on the definition of multivariable functions and their derivatives. Why is that? It is because all optimization problems are expressed in the form of multivariable functions. If you acquire an accurate definition of multivariable functions and the concept of differentiation, the theoretical approach to the aforementioned fields will become significantly easier.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is necessary to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence.

This course is a hands-on program for practicing the fundamentals of machine learning mathematics and statistics using Python. While machine learning and deep learning require programming skills, a mathematical background is essential to understand the underlying principles. Through this course, you can step-by-step master the foundational mathematics required for artificial intelligence!

You can understand the theoretical operation principle of the Kalman Filter through easy examples.