Learn how to plan, deploy and run a Machine Learning problem on AWS and Meeshkan
In this course, Meeshkan C.E.O. Mike Solomon will teach you how to do Machine Learning on Meeshkan.
Meeshkan is an easy and inexpensive platform where people can explore ideas in AI, Machine Learning and Deep Learning.
This course starts with a simple AI question: can a machine predict if a GitHub project will be successful by analyzing only the first few commits of that project?
The first section of the course will run the Machine Learning project on Meeshkan. You’ll see how quick and easy it is to do Machine Learning on Meeshkan.
The second section of the course will delve into each step of the process in detail, covering data collection, data egress, infrastructure deployment, model design, model executing and result analysis.
By the end of the course, you will be able to adapt the course materials to design, run, and explore your own Machine Learning models using public APIs and the Meeshkan Machine Learning service.
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