The main trend of the last few years,Of course, we can call neural networks, machine learning, and everything related to them. And there are serious reasons for this, because recently neural networks have been surprising with their skills. Not only can the neural network already draw portraits of people by their voices alone and “revive” the portraits of Dostoevsky and Marilyn Monroe, so it is still able to show how you will look in 20, 30 and even 50 years! Of course, all this is done by more than one neural network - in the world there are many similar developments that Data Science specialists are engaged in.
- 1 How did the neural networks
- 2 What are the neural networks
- 3 How to teach neural networks
- 4 Can I learn to work with neural networks myself
How neural networks appeared
It all started with scientists trying to bring the principle closer.computer works to a person’s way of thinking. This took decades of research, and in the end it became possible with the help of neural networks - computer systems assembled from hundreds, thousands or millions of artificial brain cells that are able to learn and act on a principle that is extremely similar to how the human brain works.
Of course, one cannot say that a neural network isThis is an exact artificial copy of the brain. It is important to note that a neural network is primarily a computer simulation: such networks are created by programming conventional computers, in which conventional transistors combined in logical connections operate in the traditional way.
What do neural networks consist of
A conventional artificial neural network consists oftens, hundreds, thousands or even millions of artificial neurons. They are called blocks - they are arranged in layers, where each block is connected to the neighboring one. There are input blocks with which the neural network receives information, and output blocks - they are just responsible for the processing result.
When the network learns, samples of information"Fed" to her through the input blocks, and then get to the output blocks. For example, you can show the neural network a huge number of photos of chairs and tables, explaining to her the difference between these pieces of furniture as much as possible. And then ask her to recognize the object in the picture, which shows the closet. Depending on how effectively you trained the neural network, it will try to classify what it saw as a category based on its experience.
How to teach neural networks
Neural networks are trained "by the reverse methoderror propagation. " With its help, it is possible to compare the output data with the data that was expected to be received, and use the differences between these data to make changes in the connection between the blocks occupied in the network. The more a neural network learns, the faster it becomes to reduce to zero the difference between the desired and actual results.
Once the neural network has been trained withUsing enough examples, she reaches the stage where you can provide her with a whole new set of input data that she has never seen and monitor her reaction.
Areas of use of neural networkslimited. So, they can search the picture or act as a voice assistant - the same Alice is already as close as possible in her behavior to a real person. Or calculate the likelihood of diseases, find tumors in the pictures, fight fraudsters and so on.
Can I learn to work with neural networks myself
Previously, such an opportunity was provided onlyscientists, because the developments in the field of neural networks and machine learning were too "raw". But now any technology company generates a huge amount of data that needs to be processed in order to then optimize the business and analyze prospects on its basis. For this and other tasks related to neural networks and machine learning, we need Data Science specialists.
How to become one? It is almost impossible to do it yourself. This is a serious specialization, which requires interaction with those who are already working in this field. Therefore, the SkillFactory data school opens a new set for the full course on Data Science. As part of the course, industry professionals, including Yandex and NVIDIA employees, teach the intricacies of work that are not written in textbooks.
With this course you can master science inworking with data from scratch, even if you've never done programming in your life. It allows you to get all the skills needed by a Data Science specialist - from Python programming, including in-depth study of Pandas to analyze data, to machine learning, deep learning and data mining. The course consists of about 20% of theory and 80% of practice, since only with real examples is it possible to become a pro in this field.
In the learning process, you can create your ownprojects in the field of image recognition, NLP and scoring. Together with teachers and mentors you will understand the details of the work and get the necessary feedback. In addition, SkillFactory helps with job placement and recommend internships at large companies. For example, graduates get the opportunity to work at Alfa Bank, Bayer, Henkel, Sberbank and other leading organizations.
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