Machine Learning with Scikit-learn | Scikit-learn using Python | Intellipaat
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In this machine learning with scikit-learn video you will learn what is machine learning, types of machine learning, what is classification, common classification problem, what is scikit learn, why use scikit learn, and how to build scikit learn using python in machine learning in detail.
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👉Following topics are covered in this video:
00:00 - Machine Learning with Scikit-learn
01:42 - What is Machine Learning?
04:45 - Types of Machine Learning
13:11 - What is Classification?
15:46 - Common Classification Problems
18:27 - Popular Classification Algorithms
22:24 - What is Scikit Learn?
26:23 - Why use Scikit Learn?
28:06 - Steps in Building a Classifier
33:09 - Hands-On
🔗 Watch Machine Learning video tutorials here: http://bit.ly/2F1Bhqt
📕 Read complete Machine Learning tutorial here: https://intellipaat.com/blog/tutorial/machine-learning-tutorial/
⭐ Get Machine Learning cheat sheet here: https://intellipaat.com/blog/tutorial/machine-learning-tutorial/mllib-cheat-sheet/
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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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