인프런 - 라이프타임 커리어 플랫폼

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 linear algebra, which is essential for machine learning/deep learning research.

This is a lecture where you easily learn important mathematical concepts used in games. People who know math well take that knowledge for granted, so they cannot teach under the assumption that you know nothing. I will explain from a beginner's perspective, truly treating you as someone with no prior knowledge.

This is the optimization theory required for AI/deep learning, computer vision, computer graphics, etc. Optimization Theory 1 mainly deals with the definition of multivariable functions and differentiation of multivariable functions. Why is that? Because all optimization problems are expressed in the form of multivariable functions. If you acquire the exact definition of multivariable functions and the concept of differentiation, the theoretical approach in the above fields will become considerably easier.

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

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 dropout in school? They say math is important in AI, but are you at a loss as to how to approach it? The reason why math is important in AI is because math is used in the computational process of AI (machine learning and deep learning). To provide an easy explanation of differentiation, linear algebra, and probability and statistics for understanding AI, it is composed of easy explanations using graphs (coordinates) rather than mathematical solutions.

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence!

This course is a course that practices the basics of machine learning mathematics and statistics using Python. Machine learning and deep learning require programming skills, but they also require a mathematical background to understand the principles. Through this course, you can gradually learn the basic mathematics required for artificial intelligence.