Introduction to Machine Learning | What is Machine Learning | Supervised and Unsupervised Learning

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Опубликован в 30 Nov 2019 / В Фильмы

In this introduction to machine learning video you will learn what is machine learning and how does it work, how we can make learning to mmachines,hat are the various types of machine learning algorithms like supervised and unsupervised learning with machine learning examples so that you understand the concepts well. For more details on the same video click on the given URL: http://bit.ly/33E3Fsl.

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Following topics are covered in this machine learning for beginners video:

00:09 - what is machine learning
01:47 - supervised learning vs unsupervised learning
01:52 - supervised learning
03:12 - unsupervised learning

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Got any questions about supervised learning vs supervised learning? Ask us in the comment section below.
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Why should you watch this machine learning tutorial?

Machine learning is one of the fastest growing arms of the domain of artificial intelligence. It has far reaching consequences and in the next couple of years we will be seeing every industry deploying the principles of artificial intelligence, machine learning and deep learning technologies at scale.

Who should watch this machine learning tutorial video?

This machine learning tutorial is for everybody right from professionals in analytics, data science domains, ecommerce, or in search engine domains. If you are a Software professionals looking for a career switch and fresh graduates then also you can watch this tutorial.

Why machine learning is important?

Machine learning might just be one of the most important fields of science that we are just moving towards. It differs from other science in the sense that this is one of the one domains where the input and output are not directly correlated and neither do we provide the input for every task that the machine will perform. It is more about mimicking how humans think and solving real world problems like humans without actually the intervention of humans. It focuses on developing computer programs that can be taught to grown and change when exposed to data.

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