How it all began …
My love for smart machines started in the days of my childhood, when I used to dream about smart robots transforming the future. This vision became even stronger when I was exposed to wonderful sci-fi movies like I-Robot and Transformers. It was then, when I had decided to go for the STEM fields, and chose Computer Science as the true love of my life. Ever since, that relationship has remained loyal and strong.
Moving on …
Two months have passed since I completed the online offering of Stanford’s machine learning (ML) course. This is the one course which changed my life, and made me drill to the fascinating depths of the world of ML.
The course instructor, Prof. Andrew Ng, IMHO, is one of the best teachers in the field. He excels at the art of teaching really difficult concepts with relative ease. He follows the learning-by-doing paradigm, and truly makes everything seem very easy.
Alongside that, I took Prof. Yaser Abu-Mostafa’s “Learning From Data” course offered online on edX, which was more focused on the theoretical (mathematical) aspects of ML. That sudden exposure to seemingly complex and dirty theory wasn't overwhelming because of the familiarity gained by Prof. Ng’s course.
The end result was that I scored excellent grades on both the courses, and made two medium-sized projects based on the learned concepts. Currently, I’m taking a course on advanced linear algebra, which will bring more clarity to the under-the-hood stuff in the complex world of ML.
I would strongly recommend both the above mentioned courses as a starting point in ML, after which you are free and enough-motivated to find your own way. Plus, there has been a recent shift towards data science and big data all around the world, and the industry is offering new, high paying positions for expert data scientists.
Lessons learnt …
Learning the nuts-and-bolts of ML is not a trivial task. Just completing a course or two wont do much good unless you get your hands dirty. Go and make some small and basic projects to gain experience.
One must have sheer dedication towards the subject, and must learn to befriend large amounts data. Good luck for your journey in the world of ML. May the Neural-Net be with you. :P
Originally published on my blog.