Why Learn Machine Learning?
Experts say that in the future, things like machine learning and artificial intelligence have unlimited potential. So it is important to acquire skills in such technology sector. This kind of technology is making our lives inadvertently easy. We are becoming dependent on such technology. For example, when you give voice commands over the phone or ask to search the Internet for pictures, machine learning can produce the results you want. Recently, the professional social networking site LinkedIn released a list of the most in-demand skills next year in some countries, including the United States. The annual Emerging Jobs report from LinkedIn reported that the demand for artificial intelligence and data science positions in the industrial sector has risen at the top of the most demanding list in the US, which will increase more in the future. This year, Mark Zuckerberg, founder and CEO of Facebook, spoke of plans to update the technology world. His list also had machine learning.
Technology analysts predict that by 2020, job opportunities in the technology sector are expected to increase by 12 percent. This will open the door to more new jobs in front of the IT sector professionals. Artificial Intelligence or AI will be important next year. Leaders of technology, such as IOs, CTOs, product heads, etc are experienced in AI technology. Those teams of AI specialists who show skills in managing, data science and creating innovative products will move forward. Applied machine learning is one of the skills that will be used next year. At present, the importance of data science is increasing rapidly. They will be more in demand if they can demonstrate their ability to use the data.
What is Machine Learning?
The computer is given the ability to learn anything without writing any program about it in advance - that's machine learning. Because of the ability to learn from the computer, anything the computer can do very easily. In other words, if as the number of computer games increases, win rate increases, then the computer is really learning. It means that it is learning to play, and that it itself is learning machine learning.
The basic principle of machine learning is to accurately extract a specific data pattern or model from a large amount of data. Then use it to classify new information, known as 'classification'. Why this classification needs to be done? The answer is - this classification requires a lot of data for a programmer to understand, so that the program will be able to understand and classify properly.
The areas of application of machine learning are - speech recognition, image recognition and estimation.
Speech recognition: Speech recognition can be transformed into text by listening to people through software applications. The machine learning application features speech signals. Specific words or sounds can be distinguished by dividing these signals into different sections. These speech signals are created by calculating different times and frequencies.
Image Recognition: Another important application of the machine learning application is to work on the image recognition process. Often objects are defined as digital images. The digital image is calculated by counting the pixels of each image. It works in two ways: face detection and character detection.
Assumptions: Machine learning and artificial intelligence can be used to estimate a subject. For example, machine learning can be used to predict whether a person will repay the loan before giving a bank loan. The use of specific information is required to evaluate the feasibility. In this case, the role of data analysts is to play.
Technology analysts predict that by 2020, job opportunities in the technology sector are expected to increase by 12 percent. This will open the door to more new jobs in front of the IT sector professionals. Artificial Intelligence or AI will be important next year. Leaders of technology, such as IOs, CTOs, product heads, etc are experienced in AI technology. Those teams of AI specialists who show skills in managing, data science and creating innovative products will move forward. Applied machine learning is one of the skills that will be used next year. At present, the importance of data science is increasing rapidly. They will be more in demand if they can demonstrate their ability to use the data.
What is Machine Learning?
The computer is given the ability to learn anything without writing any program about it in advance - that's machine learning. Because of the ability to learn from the computer, anything the computer can do very easily. In other words, if as the number of computer games increases, win rate increases, then the computer is really learning. It means that it is learning to play, and that it itself is learning machine learning.
The basic principle of machine learning is to accurately extract a specific data pattern or model from a large amount of data. Then use it to classify new information, known as 'classification'. Why this classification needs to be done? The answer is - this classification requires a lot of data for a programmer to understand, so that the program will be able to understand and classify properly.
The areas of application of machine learning are - speech recognition, image recognition and estimation.
Speech recognition: Speech recognition can be transformed into text by listening to people through software applications. The machine learning application features speech signals. Specific words or sounds can be distinguished by dividing these signals into different sections. These speech signals are created by calculating different times and frequencies.
Image Recognition: Another important application of the machine learning application is to work on the image recognition process. Often objects are defined as digital images. The digital image is calculated by counting the pixels of each image. It works in two ways: face detection and character detection.
Assumptions: Machine learning and artificial intelligence can be used to estimate a subject. For example, machine learning can be used to predict whether a person will repay the loan before giving a bank loan. The use of specific information is required to evaluate the feasibility. In this case, the role of data analysts is to play.
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