Updated 10/2022
Genre: eLearning | MP4 | Video: h264, 1280×720 | Audio: AAC, 48.0 KHz
Language: English | Size: 11.0 GB | Duration: 173 lectures • 19h 29m
Learn To Build Machine Learning Projects Practically
What you’ll learn
Real life case studies and projects to understand how things are done in the real world
Implement Machine Learning Algorithms
Learn to create machine learning models
Learn best practices for real-world data sets.
Requirements
basic knowledge of machine learning
Description
Machine learning has inserted itself into the fiber of our everyday lives – even without us noticing. Machine learning algorithms have been powering the world around us, and this includes product recommendations at Walmart, fraud detection at various top-notch financial institutions, surge pricing at Uber, as well as content used by LinkedIn, Facebook, Instagram, and Twitter on users’ feeds, and these are just a few examples, grounded directly in the daily lives we live.
This being said, it goes without saying that the future is already here – and machine learning plays a significant role in the way our contemporary imagination visualises it. Mark Cuban, for instance, has said: “Artificial Intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise you’re going to be a dinosaur within 3 years.”
Machine learning makes a mockery of anything that can be called “important” – both at a financial as well as a global scale. If you are looking to take your career to another level, Machine Learning can do that for you. If you are looking to involve yourself in something that will make you part of something that is global as well as contemporary relevance, Machine Learning can do that for you as well.
Machine learning covers significant ground in various verticals – including image recognition, medicine, cyber security, facial recognition, and more. As an increasing amount of businesses are realising that business intelligence is profoundly impacted by machine learning, and thus are choosing to invest in it.
Netflix, to take just one example, announced a prize worth $1 million to the first person who could sharpen its ML algorithm by increasing its accuracy by 10%. This is sureshot evidence that even a slight enhancement in ML algorithms is immensely profitable for the companies that use them, and thus, so are the people behind them. And with ML, you can be one of them!
The best machine learning engineers these days are paid as much as immensely popular sports personalities! And that’s no exaggeration! According to Glassdoor, the average machine learning engineer salary is 8 lakhs per annum – and that’s just at the starting of one’s career! An experienced machine learning engineer takes home anywhere between 15 to 23 lakhs per annum.
Who this course is for
Beginners in machine learning
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