Hi! . I’m Harsh Gadgil, a machine learning engineer residing in the beautiful city of Toronto, Ontario for the foreseeable future. I blog (or, at least intend to) about data science, software development, technology and life. Welcome to my blog, feel free to look around! Oh, and in case you’re wondering,
opensorceror is my GitHub username.
More About Me
I currently work as a machine learning engineer at Bell Canada. I graduated with a masters degree in Computer Science in April 2017, specializing in Data Mining, at the University of Guelph. I also hold a Bachelor’s degree in Computer Engineering from the University of Pune. Due to my engineering background, I’m deeply passionate about building solutions to complex problems to improve people’s lives. Due to my science background, I enjoy critically reasoning about the technical nuances and empirical evaluation of such solutions.
What I Do
- Reading: Due to my Masters studies, I had lost touch with books for a while. A recent Kindle purchase sparked the dormant love of reading and now I’m hooked. I mostly read mystery/thriller novels. A great recent read was A Girl on the Train by Paula Hawkins. Due to my recent interest in creating this blog, I’m currently struggling to find time to read The Heist by Daniel Silva. I also enjoy reading about technology and politics. Yes, I agree, Wired should stick to technology articles only.
- Watching: I enjoy both real science and fictional science…anything with science really. I’m an avid viewer of PBS Spacetime. Matt O’Dowd explains mind-boggling physics concepts about the nature of reality in relatively easier to understand ways. One of my all time favorite space documentaries is Cosmos - A Spacetime Odyssey hosted by the legendary Neil deGrasse Tyson. A new favorite is Planet Earth II, which displays breathtaking UHD footage of wildlife on our wonderful, fragile planet.
- Learning: In my spare time, you can often find me cooking, traveling or watching videos on Khan Academy and taking (or rather, trying to find time to take) courses on Coursera.
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