I finally decided to learn Machine Learning seriously. This is my last term at Ramaiah University, and I have a major project as well as a course on Data Analytics to complete my degree. I decided to spend some time learning machine learning to which I have very little exposure (I did have multiple courses on it which were mandatory but I only learnt enough to pass exams). Plus it will be something exciting and practical. I did not want to spend time solving equations and calling myself a machine learning engineer. (People who want to dig deeper and have an interest in it should. It was for me.) I wanted to build stuff and know enough theory to apply it.

A good course that had a good mix of theory and practice was Andrew NG’s Machine Learning course. It was a tour of basic to advanced machine learning concepts with hands-on assignments to solidify the learning. I had a lot of fun with the course as it was a totally asynchronous course where I could learn from the recorded lectures and solve assignments on my own time.

I highly recommend Kaggle to learn practical aspects of machine learning and apply them. I will create a separate post with good resources to learn machine learning and build products with them. If you are interested in theory and want to write papers or get into a Ph.D. Programme in the same, by all means, goes ahead with classic courses from MIT and Standford, which I will also link in the post. But for the rest of us old school Software Engineers, practical knowledge will do.

I will post the link to the post below when it is up.