What technology does artificial intelligence mainly learn?

Artificial intelligence is an interdisciplinary subject, including many disciplines. You need to know computer knowledge, information theory, cybernetics, graph theory, psychology, biology, thermodynamics, and have a certain philosophical foundation and scientific methodology as a guarantee. The latest version of the artificial intelligence learning route is as follows:

First of all, you need mathematical foundation: advanced mathematics, linear algebra, probability theory, mathematical statistics and stochastic process, discrete mathematics, numerical analysis;

Secondly, it needs the accumulation of algorithms: artificial neural network, support vector machine, genetic algorithm, etc.

Of course, algorithms are needed in various fields. For example, if you want a robot to navigate and map in a location environment, you need to learn SLAM.

1. To analyze artificial intelligence from basic disciplines, we should mainly study mathematics, computers, algorithms, psychology, statistics and probability theory. Of course, these are mainly basic. If you want to further your studies, you have to dabble in more vertical industries. For example, the artificial intelligence of sociology is inseparable from social science, and the artificial intelligence of economics is inseparable from finance and economics.

2, artificial intelligence machine learning direction

Deep learning

pattern recognition

Computer vision

Wait a minute. Do not expand, Baidu yourself.

3. Artificial intelligence has a bright future. Artificial intelligence has been included in the national long-term development plan. In the future, no, now artificial intelligence has penetrated into all aspects of production and life.

At present, the learning contents of artificial intelligence major are: machine learning, introduction to artificial intelligence (search methods, etc. ), image recognition, biological evolution, natural language processing, semantic web, game theory, etc.

The compulsory prerequisite courses mainly include signal processing, linear algebra, calculus and programming (with data structure foundation). Judging from the above professional courses, there is still a lot of knowledge related to artificial intelligence to master.

From a professional point of view, machine learning, image recognition, and natural language processing are all great directions. As long as you master one of them, it is already very powerful. So don't read a lot of content, some content you just need to master. What you need to choose is a direction of in-depth research. In fact, strictly speaking, artificial intelligence is not difficult to learn, but it is not easy to learn. It needs a certain mathematical foundation and a period of accumulation.