AI branches

Hello, everyone, welcome back to my course, Artificial Intelligence in Bioinformatics. And this is the second week of this course. For the content of this course, I will cover the fundamentals and applications of Artificial Intelligence, AI, as well as to show you how you can implement some AI models using very simple technique. And for the applications that I use in this course. I will use Weka. And let’s go to the outline of this course. For the first one, I try to show you about some of the fundamentals of AI and what are different models of AI. And for the second one, how you can implement the machine learning algorithms using Weka.

And the third part is the demonstration of how you can use machine learning outcomes in Weka. And the last one, I try to show you a lot of machine learning outcomes like some of the simple algorithms in machine learning. And let’s start with the first part, fundamentals of AI. So what is the AI? Some of the practical applications of AI? I already showed you in the last session. And here, I try to give you a more detailed definition of AI, like you already know about some applications, like email filter, like auto trading card, or even also some of the face recognition applications. So what is the AI? And I take definitions to show you what is the AI here.

AI refers to the simulation of human intelligence in the machine that are programmed to think like humans and mimic their actions. So the term may also be applied to any machine that exhibits trails associated with a human mind such as learning and problem solving. So you can think that AI means that you can try to solve the …that you try to show the machine how you can learn the information from the humans and mimic their actions. How many branches of AI? Just look very similar to the bioinformatics. I also show you about the branches of AI, and which branch that you can use in bioinformatics. For the first branch of AI, very famous is the machine learning.

Machine learning include like supervised learning, unsupervised learning, or even nowadays, you can see that many people they try to use the deep learning. And for the second branches of AI is natural language processing. This is NLP. It is the branch that mostly focuses on to process natural language. And in natural language processing, you can have some different studies just like content instruction, like classification, machine translation, question answer. And there are these two these two branches we use a lot in bioinformatics. And I also try to show you how you can implement some of these, some of these studies of the branch in bioinformatics.

However, in artificial intelligence, there are also have some different branches such as expert systems, or computer vision, or like speech, planning and robotics. However, I will not cover it in this course, because I want to focus on applying applications of AI in bioinformatics.