Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 48.0 KHz
Language: English | Size: 5.51 GB | Duration: 15h 38m
Learn Importance of Machine Learning With All Libraries Like Numpy, Pandas, MatDescriptionlib, Sklearn
What you'll learn
Learn About Machine Learning Algorithms
Improve your data science and coding resume
Create robust data science medk
Description
ecause of new computing technologies, machine learning today is not like machine learning of the past. It was born from pattern recognition and the theory that computers can learn without being programmed to perform specific tasks; researchers interested in artificial intelligence wanted to see if computers could learn from data. The iterative aspect of machine learning is important because as models are exposed to new data, they are able to independently adapt. They learn from previous computations to produce reliable, repeatable decisions and results. It's a science that's not new - but one that has gained fresh momentum.
While many machine learning algorithms have been around for a long time, the ability to automatically apply complex mathematical calculations to big data - over and over, faster and faster - is a recent development. Here are a few widely publicized examples of machine learning applications you may be familiar with:
The heavily hyped, self-driving Google car? The essence of machine learning.
Online recommendation offers such as those from Amazon and Netflix? Machine learning applications for everyday life.
Knowing what customers are saying about you on Twitter? Machine learning combined with linguistic rule creation.
Fraud detection? One of the more obvious, important uses in our world today.
Who this course is for:
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