How to get started with artificial intelligence? How to get started with artificial intelligence?

The learning content includes the basics of mathematics, the accumulation of algorithms, and programming languages. Mathematics needs to learn high mathematics, linear algebra, probability theory, discrete mathematics, etc., algorithm accumulation needs to learn artificial neural networks, genetic algorithms, etc., and also need to learn a programming language, through the programming language to implement algorithms, and you can also learn the basic hardware content of computing.

2. Professional application fields of artificial intelligence.

The application fields are very wide, mainly image recognition, game theory, introduction to industrial intelligence, machine learning, etc., of course, if you want to develop in these fields, you also need to learn some signal processing, calculus, data infrastructure and other knowledge content, to ensure that there is a certain theory to support the use process.

3. Artificial intelligence employment prospects.

With the development of intelligence, artificial intelligence technology will be gradually applied and popularized in the Internet industry, and the technology will be applied to the Internet of Things, big data and other industries, so the employment demand will continue to expand, and we will frequently interact and communicate with agents, which is also the development trend of the future social production environment, which requires us to meet the needs of the development of the times.

With the continuous development of artificial intelligence, new requirements have been put forward for us, so the relevant basic content of artificial intelligence must be learned, and mastering artificial intelligence technology will become an inevitable trend.

1.Basic knowledge of advanced mathematics.

First of all, if you have no foundation, you should first learn the basic knowledge of advanced mathematics thoroughly, starting from basic data analysis, linear algebra and matrices, etc.

2.Have a certain level of English.

Think about it, if you can't even understand basic English words, how can you write **? After all, ** is made up of English words. So, let's improve our English, it's very, very important.

Python has rich and powerful libraries. Often nicknamed the glue language, it makes it easy to link together various modules made in other languages, especially C++. For example, the graphics rendering module in a 3D game has particularly high performance requirements, which can be rewritten in C C++ and then encapsulated into an extension library that can be called by Python.

This is also a must-have knowledge of artificial intelligence.

In addition, it should be mentioned that machine learning belongs to a branch of artificial intelligence, which allows machines to get rid of their dependence on human instructions and carry out independent learning according to certain algorithms.

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Artificial intelligence is a discipline that studies the use of computers to simulate certain human thinking processes and intelligent behaviors (such as learning, reasoning, thinking, planning, etc.), mainly including the principle of computer intelligence, manufacturing computers similar to human brain intelligence, so that computers can achieve higher-level applications. AI will involve disciplines such as computer science, psychology, philosophy, and linguistics. It can be said that almost all disciplines of natural science and social science have far beyond the scope of computer science, and the relationship between artificial intelligence and thinking science is the relationship between practice and theory, and artificial intelligence is at the level of technical application of thinking science, which is a branch of its application.

From the point of view of thinking, artificial intelligence is not limited to logical thinking, to consider image thinking, inspired thinking in order to promote the breakthrough development of artificial intelligence, mathematics is often regarded as the basic science of a variety of disciplines, mathematics has also entered the field of language and thinking, artificial intelligence disciplines must also borrow mathematical tools, mathematics not only plays a role in the scope of standard logic, fuzzy mathematics, etc., mathematics into the discipline of artificial intelligence, they will promote each other and develop faster.

Artificial intelligence, also known as intelligent machinery and machine intelligence, refers to the intelligence displayed by machines made by humans. In general, artificial intelligence refers to the technology that presents human intelligence through ordinary computer programs. Through advances in medicine, neuroscience, robotics and statistics, some believe that countless human occupations are gradually being replaced by artificial intelligence.

Basic Mathematics, Basic Computing, Artificial Intelligence Basics.

Artificial intelligence is one of the hottest outlets today, and if you want to seize this outlet, you can start from the following aspects:

2. Learning related technologies: At present, the more popular AI technologies include machine learning, deep learning, natural language processing, computer vision, etc., which can be learned by registering for classes, self-study, and participating in offline and online training.

3. Find your own interests: AI application scenarios are very wide, if you are more interested in a certain field, you can learn about the field through related **, books, experimental dates, etc. In addition, looking at other people's success stories, business investment projects, etc., will also give you new feelings and ideas.

Participate in the robot Jane Yuan Ant Football Battle (social activities, personal hobbies), apply robots to physical stores and online stores, assemble various sensors for drones (commercial applications), develop your own AI products (entrepreneurship), etc.

With the fiery development of artificial intelligence, more and more people have joined in the learning of artificial intelligence, and there are many friends who have decided to learn artificial intelligence before they must have understood what knowledge artificial intelligence needs to learn, and what level they need to master.

Learn about artificial intelligence.

The first most important thing to learn artificial intelligence is to master a programming language, you have to have the ability to program, of course, if you don't know the programming language, it doesn't matter, it's not too late to learn a programming language, the first programming language for artificial intelligence is the python language, which can be said to be the first thing in artificial intelligence today.

Of course, this is the most important thing to master, and then for the principles and technologies of algorithms, etc., the professional skills and knowledge corresponding to different fields are also different, and the knowledge that needs to be learned in different fields is also very different, such as machine vision, fingerprint recognition, face recognition, etc. Changping Beijing IT Training believes that artificial intelligence is a discipline that contains many fields, and when you come to learn artificial intelligence, are you mentally prepared, can you persist in learning hard?

I really want to learn artificial intelligence, but the tuition fee for the training class is too expensive, and the family conditions are not particularly good, so I can't bear to use my parents' meager work without money. I want to find a good job through self-learning artificial intelligence, support my family, and change my destiny. So how do you learn to get started with AI on your own?

Absolutely, please read below.

Self-study is generally through reading books and getting started, and there is still a lot of knowledge about artificial intelligence on the Internet. However, it is no exaggeration to say that Beijing Peking University Jade Bird found that many zero-based beginners self-taught artificial intelligence are easy to get into the fog if they directly read books, which can be said to be an artificial intelligence beginner from giving up. Yi seed cycle.

Therefore, it is recommended to first have a general understanding of what artificial intelligence is, and then to recruit ** to see what kind of skills are needed by enterprises now, and have a general direction. It is best for beginners to learn artificial intelligence through **. For example, Professor Ng Anda's machine learning, MIT's linear algebra**, and so on.

Come to our official website to see what artificial intelligence is going to learn.

The learning method of artificial intelligence is as follows:

1) Learn the basic knowledge of advanced mathematics thoroughly.

Starting from basic data analysis, linear algebra and matrices, etc., only after laying a good foundation can you learn later, and you can't learn one piece without logic.

2) Learn python well

Python has a rich and powerful library that makes it easy to link together various modules made in other languages, especially C++. For example, the graphics rendering module in a 3D game has particularly high performance requirements, which can be rewritten in C C++ and then encapsulated into an extension library that can be called by Python. This is also a must-have knowledge of artificial intelligence.

3) Master machine learning algorithms (focus).

For machine learning algorithms, it is necessary not only to understand them, but also to be able to use them.

4) Improve learning deep learning algorithms.

By the time the third step is almost complete, you're already in the field. Because machine learning is a multi-disciplinary discipline, involving multiple disciplines such as probability theory, statistics, and algorithm complexity. It is the core of AI and the fundamental way to make computers intelligent.

You can then learn the content shown in the figure below.

5) Lead Worm Actual Project Trial.

The learning process of artificial intelligence cannot be without the operation of actual project application. When you're done with deep learning. You can find some practical examples to experiment with some of your learning.

The recommendation algorithm is a kind of algorithm in computer science, which uses some behaviors of the user's object wheel to infer what the user may like through some mathematical algorithms, which plays a certain role in judging the AI species.

1. Understand the basic knowledge of artificial intelligence: The first step in learning artificial intelligence is to understand the basic concepts of artificial intelligence, such as machine learning, deep learning, neural networks, data mining, etc. Basic knowledge can be acquired by reading various materials, books, courses, etc.

2. Learn programming skills: Learning programming skills is the basis for carrying out AI research and practice, and in order to write high-quality and efficient AI programs, you must master programming skills. Focus on mastering the basic knowledge of Python language, data structures, algorithms, etc.

3. Participate in artificial intelligence-related courses: Many universities and ** platforms provide relevant courses, and it is highly recommended to participate in these courses, which will be of great help to improve your artificial intelligence skills and knowledge system accumulation.

4. Practice and exploration: Learning artificial intelligence should focus on practice and exploration, practice is the best way to test theoretical knowledge, and practical experience can be increased by developing ** or participating in projects.

5. Pay attention to cutting-edge technology: The technology in the field of artificial intelligence is changing very fast, and we must always pay attention to new technologies, such as GAN, BERT, YOLOV5, etc., to maintain cutting-edge knowledge and technical team code Li insight.

Artificial intelligence is a hot spot in the field of science and technology in recent years, and with the development of big data, machine learning (including deep learning) has developed to a certain extent, and is now widely used in autonomous driving and other fields. With the application of the Internet of Things, big data and cloud computing, the field of artificial intelligence is believed to release many development opportunities. Next, Jintou will introduce how to learn artificial intelligence in the middle of the day.

First: Start with the basics. Research in the field of artificial intelligence focuses on six areas, namely natural language processing, machine learning, computer vision, knowledge representation, automatic reasoning, and robotics, which vary in focus but require an important foundation, namely mathematics and computer foundations.

One of the core problems of artificial intelligence is the mathematical problem, specifically the design problem of the algorithm, and the specific implementation of the algorithm is related to computer knowledge. Therefore, among the many disciplines involved in artificial intelligence (philosophy, mathematics, computers, neurology, economics, languages, etc.), the foundations of mathematics and computers are very important for R&D personnel.

Second, understand the R&D content and R&D methods of artificial intelligence. More than 60 years have passed since the research and development of artificial intelligence, and now Hu Cong is still in the early stage of the development of the industry, and now machine learning, computer vision and robotics are more popular fields. Before learning this specific knowledge, there should first be a holistic cognitive process of artificial intelligence, and it is a good way to understand the development history of artificial intelligence.

Third: Start with big data. For people with a weak foundation, entering the field of artificial intelligence through big data is a more realistic path.

Big data technology has matured and is currently in the early stage of application, and big data, as an important foundation of artificial intelligence, will play a great role in promoting the development of artificial intelligence in the future. As one of the important means of data analysis, machine learning is currently widely used in the field of big data, so it is a better route to enter machine learning through big data and fully enter the field of human banquet and mountain engineering intelligence.