Do you need math to get into ARTIFICIAL intelligence
The main field of artificial intelligence are deep learning, natural language processing, computer vision, intelligent robot, automatic program design, data mining, etc, all these areas related to the data, and the huge data can’t depart from the support of mathematical calculation, especially for the development of artificial intelligence data, need more mathematical theory and mathematical theory innovation.
Compared with APP development, Web development and game development, ARTIFICIAL intelligence is a mathematical knowledge intensive direction. In various books, papers, algorithms are filled with a large number of mathematical formulas. All fields of AI incorporate mathematical knowledge from calculus, linear algebra, probability theory, mathematical statistics, optimization theory, information theory, approximation theory, discrete mathematics, and more.
Mathematics is a necessary foundation for artificial intelligence. You need to understand the internal logic of an algorithm. You can’t do without mathematics. If you don’t have a basic knowledge of math, you can probably start running algorithms, tuning parameters, etc. But what if it doesn’t work? If you don’t know the math, it’s hard to optimize. Math determines how far you can go in ai technology.
In fact, the mathematics required by artificial intelligence is not particularly advanced, such as specialized mathematics professional of that kind, it is not necessary. As long as you have a college degree in science and engineering, you should know a lot of the math required for ARTIFICIAL intelligence. It is only possible to understand not thoroughly at that time, or a long time not to see, need not, do not review, a lot of knowledge into only heard but do not understand. How to calculate mutual information, how to iterate Newton’s method…… Do you remember.
What mathematical knowledge should you have as an ARTIFICIAL intelligence engineer
As an AI engineer, if you want to go further in the field of mathematics, whether you want to study systematically or to find out the gaps, I recommend this book “Mathematical Foundation of ARTIFICIAL Intelligence”.
The Mathematical Foundation of ARTIFICIAL Intelligence systematically combs the mathematical knowledge needed for artificial intelligence. Based on calculus, linear algebra, probability theory and mathematical statistics, it introduces function approximation, optimization theory, information theory and graph theory in depth, and gives their experimental cases in artificial intelligence algorithms. It can be the math primer you want to learn about ARTIFICIAL intelligence, or it can be a handy reference book that you can flick through to help you overcome difficulties.
