Artificial Intelligence & Machine Learning

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What is AI/ML?
Artificial intelligence is the actual newfound fire. If we make this fire even bigger and warm ourselves with this fire, you can be sure that there will be a huge technological change in the future. This will completely change our lives.
To begin with, we should turn our faces to the second word that is intelligence before looking at artificial intelligence. What does intelligence mean? Why do we want machines to act like us? I'll try to describe them as much as possible. Intelligence is the behavior of learning, problem-solving, testing what they have learned. AI is the name given to systems that can replicate human mental abilities such as the learning and testing process. Such a capability at least includes the ability to perceive language and speech and to think strategically.
The process of learning and testing artificial intelligence works as follows.
1 - Necessary data are collected.
2 - Data is cleaned and made available for analysis.
3 - Data is analyzed and learning datasets are now created.
4 - Algorithms and codes that can reach the correct result at the best performance are written so that
artificial intelligence can test what it has learned and produce results with high accuracy.
5 - Then, this training data is given to the computer, and how much it learned is tested.
The processes of training and testing this data can be traced in a cycle. In this way, we can give X data and know-how accurately the information he learned from this X data makes predictions. Train and test results are not always the same, and they should not be. If they are the same, mistakes are made somewhere. The data given to the computer can consist of structured or unstructured data.
These are not important, but the main thing is to learn how accurate it is to be able to use this data and to observe what it can achieve in the future using this data. On the other hand,I will not pass on machine learning with Tom Mitchell's explanation, because it can sound very complex.
In short, machine learning is the discipline related to the implementation of software that can learn on its own.Machine learning requires multiple machines to communicate with each other without any code, you can imagine how exciting this situation is.For example, if you have a lot of work and you can't clean your house or even cook yourself, imagine a robot doing that for you, or if you were a student and a robot doing my homework for you. In fact, all of these situations seem a little difficult in today's world, but they are not impossible. We can facilitate this situation with some basic paradigms in machine learning. Machine learning can learn in two ways.
1 - Supervised Learning
2 - Unsupervised Learning
In supervised learning, we have a specific input value and output, and the machine reaches it using this input data to find this output.Things are a little different in unsupervised learning. For now, we usually work on classification, so we
only give our input data and we want to find the output by itself. In this case, there is progress by more classification.
In conclusion,Unlimited changes can be made and applied in this area, which I want to mention briefly and generally.The use of technology in this field can lead to a great breakthrough in the future and thus we can open our eyes to a very different world because AI and ML have made a place for themselves not only in simple jobs, but also in living health, transportation, social field, robotics and many other areas and thus, in fact, in the future. We will be able to use it in all areas.