Which subdivisions and what are their employment prospects?
When it comes to artificial intelligence, his current employment prospects are still very broad. Whether it is the Internet or the real industry, there is a great demand for artificial intelligence talents. Therefore, more and more people now want to get started with artificial intelligence, or want to switch to artificial intelligence. But artificial intelligence is a big direction, which can be roughly divided into five directions: data mining, computer vision, natural language processing, speech recognition, and knowledge graph. Below I will explain them separately to see if there is a suitable direction for you.
The first, data mining. It is an AI subdivision based on machine learning algorithms, and it is the most basic and the most extensive employment direction among the many directions of artificial intelligence. I used to do precision marketing in Internet advertising, so I am familiar with data mining.
Having said all that, what exactly is data mining? Data mining is simply to mine potential value from massive amounts of data. For example, the well-known story of beer cloud brewing is also based on the association rules in data mining, ABILIOALI algorithm. For many enterprises, there is a great need for talents who understand data mining. Therefore, people who understand data mining, the current employment prospects are still very good. At the same time, in terms of salary, it is generally possible to beat others with the same work experience.
The second, computer vision. It is a field based on deep learning algorithms, computer vision.
→C→O/C=CV, there are many things that can be done in this field, such as image classification targets, detection face recognition, etc.
At present, CV technology is becoming more and more mature, and there are many studies on this aspect in top international journals, so you can continue to innovate on the basis of the research of predecessors. I believe that at present, the CV area is mainly based on technological innovation. If you are a person who likes to use more brains and is willing to innovate, you can try this direction, and the employment prospects are still very broad.
Third, natural language processing. Natural language processing NLP, like computer vision CV, is also a lot of discussion in many fields of artificial intelligence. And at present, many companies also want to use natural language processing technology to carry out some text mining, machine translation, intelligent question answering, public opinion analysis, etc. So his job prospects are even better than CV.
However, at present, many companies spend a lot of money to find a good NLP talent, mainly because NLP research is more difficult, and talents who understand NLP are still very scarce in the market.
The fourth is speech recognition. I don't recommend that you pay attention to the direction of speech recognition, why? The main reason is that it has a relatively narrow employment base compared with several other artificial intelligence fields, and there are not many employment opportunities.
Speaking of this, you may not understand what speech recognition is, speech recognition is a simple understanding of a pattern recognition, the solution is to filter out the sound you want from multiple voices, such as speech recognition in WeChat chat is one of the applications of speech recognition.
The fifth is the knowledge graph. Knowledge graph is a special kind of graph data, this graph data can be understood by people, it emphasizes the ability to memorize reasoning and association. For example, my grandfather's son is an uncle, from which it can be deduced that the kinship between many entities is a social network. In fact, it can also be reasoned through the knowledge graph, and the current employment prospects in this direction are also very good.
The above are the main subdivisions of artificial intelligence, have you decided which one to engage in? Follow me in the next issue to tell you what to learn in various fields of artificial intelligence? See you in the next issue.
With the fire of artificial intelligence, more and more people are interested in artificial intelligence AI, and it just so happens that I am also a connotation in this regard. So in this video, I want to talk to you about the specific subdivisions of artificial intelligence AI.
