Machine Learning Algorithms and AI Engine Requirements

A free video tutorial from Vinoth Rathinam
Founder of Vinoth QA Academy | Automation Architect
Rating: 4.3 out of 5Instructor rating
3 courses
143,586 students
Machine Learning Algorithms and AI Engine Requirements

Lecture description

This video explains the below topics : 

What is Algorithm?

List of Machine Learning Algorithm

List of Machine Learning Tool/Engine/Framework

AI Case Study


Learn more from the full course

Welcome to Artificial Intelligence !

NON TECHNICAL COURSE specifically created for AI/ML/DL Aspirants, gives insight about Road map to A.I

48:42 of on-demand video • Updated January 2019

Basic Idea of Artificial Intelligence and Machine Learning
Prerequisites or Road map to start Machine learning project(ML)
How to choose the best programming language for AI ?
How much Mathematical knowledge needed for AI ?
Which is the best AI Engine/Tool/Framework for AI ?
Why do we need to learn Algorithm?
Types of Machine Learning Algorithms with Real time scenario examples
English [Auto]
Hello, everyone, welcome to Reno threatening I'm Territorials. In this video, we are going to learn aboard the road map to artificial intelligence in a previous video, we have already completed our discussion about programming, language, mathematical knowledge. No, all this because I bought a machine learning algorithm tools and a case study before we see machine learning. I go to them orders. I'll go to them and I'll go to them is a step by step method of solving a problem. Just guess what will be the good at them for the scenario. We have discussed in our scenario. We have decided the bad because we have three possibilities to reach the table so that suffice to step out beside the bot. Second one, go near to the table. And third step big the ball and footstep. Give it back to the person and talk to me. So we have to follow footsteps. Then only this particular problem will be solved the same way we have been blaming the algorithm based on the type of machine learning we are going to use it. We have three types of machine learning, supervised learning, unsupervised learning and reinforcement learning. These are the few famous algorithms. You can see it here. Don't be scared by seeing these many number of you go to them because we will choose the algorithm based on a project we work next. Really? Or I'll be posting their tricks to Tuesday, a project followed by the types of machine learning. At that time, you will get more clarity for time being. Now, just remember only one thing we have to choose the algorithm based on the AAA project we work. Don't come to the conclusion that we have to learn all these. I go to them. Some of their families. I would go to them like Navy Base Classification, which we use it in that GMAT to fill that spam mails. In our scenario, we have to go from one location to another location that is a kid, how to move where there are people. Then come back to me. It is similar to Google Map that we use Dextra. I go to them. It is a Dutch scientist. Me. These are all few reinforcement learning algorithms. The fourth step is we have to learn the machine learning tool framework engine. It can be called an ATV. Once we select the aid, we have to train other model. It never scenario if you think the boy can go in any way or not a possible way to be able, then each are wrong. A model, because in case if the below is replaced by a handball, what will happen to good. He will get hurt if you think he can jump. Abo Dianabol then in case if the iron ball is replaced by a tile wall, surely the boy going to hit the wall. Final conclusion. The boy must choose a way that he won't eat any object. If you train you are a mortal like this, then if you go to some other news tonight, like to take the ball in anywhere in the room. Surely a system will properly work, even though you didn't court for that scenario because you can take all decision based on its previous results. You never example that by Manny Blades might come there. Does how big the ball with the help of this brain. For him, brain is the main engine to take the final decision. Same way in AA we used a machine learning tool ah engine ah framework to get define a load book. All the big companies are spending billions of dollars on creating the EAA engine by seeing the name itself. You can guess the company name Google stands at low wages or enough the very in being an femur's eight right now which can be used in all the field. Initially the Google used Dodge. Now they have created their one AA building. Then IBM bought sandwiches or not. Very good a tool for the medical purpose. Then Microsoft and Amazon giving a very high died competition. Florida. I led that áng in chlorides, guys. If blue, which is used for automation purpose, so are you. No need to worry about creating engines framework. You can Barraclough download on to use it based on you at projected to go out. Now how does elect a proper doulas mitigating maybe while explaining about their texture. Do they project. Do we get an idea about the final step. We have to practice day yesterdays. She had, I have mentioned fewer families, case studies like real estate price prediction. That prediction then identified the fake news, which is a trending topic now. What do you have to do is just to Google these topics? You will get what? I'll go to them. Yay! Do they have used even in some case, you will get some coding Jaitapur. Hope you got an idea aboard that road map to a conclusion year program, language and a mathematical knowledge of the prerequisite, I'd need to start a project. I've read that we must learn the machine learning algorithm and machine learning tool. Didn't practice for a sample case study. Once you are confident d'abord sample case study, then you can start implementing all this Strix into your own essay topic. More than all these things, you must have a passion towards learning new stuff. Then one lead will be more interesting to work in a project. I'm sure you got an idea. Boardwalk's Yay! No, that's the end of today's issue. Thanks for watching. Happy learning.