As everyone knows, learning machine learning machines to learn how to do it. For example, we would like to learn to complete the task, or make the right prediction or acting reasonably. Learning is always made based on types of vision or data, for example ... direct experience or teaching. Therefore, in general, machine learning is about learning how to improve the future based on what has already happened.
Learning machine is used for many applications in the world for various reasons. In this article, we will see a number of Applications for Machine Learning.
1. Image Recognition
One of the most common uses of machine learning is photography. There are many situations to distinguish the product as a picture. In digital images, your measurement describes the pixel production of the image.
Under the picture in black and white, each pixel intensity serves approximately. So if the black and white picture has pixels N * N, the total number of pixels and, therefore, the size is N2.In colour image, each pixel is considered to offer 3 steps of intensities of 3 segments of the lower colour, ie, RGB. Then, the colour scheme N * N has 3 sizes N2.
Face marking: The parts can be expensive and have no faces. There may be a particular segment of everyone in a large collection of data.
Recognition of Symbols: We can divide a portion of a small piece of text, each with one characteristic. The sections can contain 26 letters of English, 10 numbers and special symbols.
2. Speech Recognition
Sound recognition (SR) is a translation of the words in the text. Also known as "automatic identification" (Casar), "Computer coding" or "voice to text" (STT).
Speech recognition, the software application recognizes speech words. The estimation of this application may be a number that represents the signal. We can divide categories with different sections into different words or dialects.
For each category, we can set up some sign or word of power at different times. Although the details of the signs are beyond the scope of the program, we can make a sign indicating the actual price. Sound recognition codes include the voter's mediator. Interfaces are voice users such as voice calling, calling, blocking home appliances. You can also use it as easy access to access, organizing documented documents, voting patterns and images.
3. Detection of the disease
ML provides methods; techniques and tools that can help solve problems and autism in different types of health. It is used primarily for clinical and interdependent bioavailability, p. predicting the spread of the disease, because of the study of health knowledge in the research, planning and support therapy, and general patient management. ML has also been used for data analysis, as seen on regularities in data so that the data is more stable, interpretation of regular data used in ICU and alarm sounds resulting in an effective and efficient monitoring.
They claim that successful implementation of LD systems can help integrate computer-based computing systems, opportunities to facilitate and improve the health professionals and, finally, improve the standard of care and the quality of health care.
In medical research, the most important thing is to know the existence of a disease including its correct identity. There is a part of every illness that is considered for consideration and the side effects that are not present in any illness. Here, machine learning improves the diagnosis of health diagnostics by analyzing patients' data.
The estimation of this application is usually the result of some medical examinations (for example blood pressure, temperature and several bloods) or health problems (such as medical imaging), presence/absences/strengths, and basic information about the patient (age, sex, weight, etc.). Based on the results of these measurements, doctors reduce the patient's presence.
4. Statistical Arbitrage
In finance, arbitrage refers to automated commercial strategies that are typically short-term and involved in the pricing. In such a way, the user attempts to implement a set of business values that are based on value-based values such as the relationship of historical relationships and the general economy variable. These steps can be produced by triage or measurement problems. The basic estimate is that the price will go through the historical average.
We use computer literacy techniques to achieve a strategic goal. In particular, we use the direct and indirect support of SRV to the value of the exchange-traded and the flow of their transactions. By using the PCA analysis to reduce the perspective of workspace, I see the money and look at the problem in the implementation of the SRV. To create trademarks, we have designed the early repetition of a medium-term financing system.
In terms of classification, parts can be sold, purchased, or not performed in all security. Given the estimation, one can try to predict the expected performance of any future security in the future. In this case, you often need to use the estimation of expectations expected to take a business decision (buy, sell, etc.)
5. Education organizations
Educational linking is a way to develop ideas about different productivity organizations. A good example is apparently unprotected and represented by the alliance. When analyzing the customer's behavioural characteristics.
Direct education: It often learns how to connect people's products, also called offenders. If you buy a buyer? Seriously, would he or she buy it? because the relationship can be identified within them. This creates contact between fish and fractions, etc. when new products are opened in the market. Recognizing these relationships, he develops a new relationship. Identification of these relationships can help with the productivity of the product. The more likely that the client will buy, it can also help a group of products to have a good package.
Physical education between machine tools is the learning of clubs. When we get an organization when looking at a lot of data sales, Big Data analysts. You can enrol the law to collect the probability test for learning about the possibilities.
6. Prediction
Consider, for example, a bank that calculates the possibility that one of the creditors can fail to repay the loan. To calculate the probability of failure, the system first needs to sort out the data available in specific groups. It is described by specific rules that were prepared by analysts.
When we make sorting, depending on the need, we can calculate the probability. The mathematical calculations for this account can be calculated for all parts of the range Prediction is now one of the best algorithms for learning the best technology. Let's take a retail sample, and we have already been able to figure out how the sales report last month/year / 5 years / Diwali / Norway. This type of report is called historical information. But now the companies are interested in knowing what will be my next month/year / Diwali, etc. So the company can make the required decision (purchasing, savings, etc.) at the time.
7. Removal
Export of Information (IE) is another machine application. It is the process of producing information in unacceptable data. For example, web pages, articles, blogs, business reports and e-mail. Coordination information holds the results produced by the release of the information.
The production process carries out a document that produces data that is organized. This result is in a limited format, such as the Excel sheet and the table of contact information. The logical issue will be the key to the key data industry. As we know, a great amount of data has been produced, which is largely unprotected. The primary challenge is to regulate unregulated data. The modification of an unstructured data form of the form is based on a format so that it can be stored in RDBMS.
In addition, in recent days, the data gathering system is also found to be changing. Before we collect data from different groups such as the End Times (EOD), but the companies now want the information as soon as it is released, that is, in real time.
8. Regression
We can also use machine learning to correct. Suppose x = x1, x2, x3, ... are variable variables and y are the result of the result. In this case, we can use machine technology to generate (y) based on variables (x). You can use a sample to show the relationship between the following ways:
Y = g (x) where g is a job that depends on the specific characteristics of the example.
For the repairs, we can use the principle of machine learning to reduce the boundaries. To close down the mistakes and calculate the possible results as possible.
We can also use machine learning to improve operations. We can choose to change the entrance to find a better way. This gives you a new and improved way to work. This is called designing a function.
At the end
Finally, machine learning is a pragmatic development of technical intelligence. Although it has a frightening effect when thinking about it, machine machines are a number of ways in which technology can improve our lives.
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