Machine Learning Practical Course: Build 30 Projects
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
Instructor
I have been working as an ML Engineer for roughly 4 years now and worked in other Data Science Jobs along the way. If you are like me once planning to transition from either your university life into the ML Engineering world or going from a different job into this exciting field. I am going to walk you through the steps that I would take if I was starting over today, on what exactly I would be focusing on, and then give you a rough time estimate on how long you should focus on each area, such that you can step by step improve your skills throughout the year. We will finish off with a lot of concrete tips on how to turn these skills into a job offer and where to actually learn them.