Welcome, 2017!

As yet another year rolls around, I’m full of anticipation about making the most of it to further my priorities, goals and interests. Looking back, 2016 was a good year. I did quite a bit a traveling, that included fulfilling my long time wish to scale Half Dome in Yosemite, and taking my first trip to Southeast Asia with a memorable visit to Thailand with my family. The year also involved my getting back to more reading and dabbling in some blogging and writing.

As we head into 2017, I’m looking forward to doing some serious technical studies and expand on my professional skill-set. As a software engineer that has been doing the “same old, same old” for a while now, exploring newer domains of knowledge will be a refreshing change of pace and kick me out of my comfort zone.

Here are some areas that I’m planning on diving into this year.

Machine Learning:

This discipline within the field of Artificial Intelligence seems to be pervading a large section of human endeavors. I’ve been seeing quite a few of my peers and ex-colleagues getting into working on cutting edge Machine Learning/Deep Learning projects. Significant number of job postings at respectable software firms have begun mentioning Machine Learning as a desirable skill. It surely seems like this is a great time to get into the field and start investing time to gain expertise in the area.

A good place to get started laying down a foundation in Machine Learning is the immensely popular online course offered by Coursera. I’ve just registered for this course that would begin on January 9, and would go on for 12 weeks, until April. Working through this course would be my primary area of focus for the first quarter of this year.

Linux Kernel:

Operating Systems have been one of my main interests, although I need to admit I can do better when it comes to acquiring a profound understanding of the internals and the various subsystems of an Operating System. Having picked up books on the Linux kernel on and off in the past haven’t been very effective. This year, I plan on doing a consummate and dedicated job at gaining a thorough understanding of the internals of the Linux Operating system. As I wrap up on my Machine Learning course, I’ll be jumping headfirst into Robert Love’s “Linux Kernel Development”.

Python:

Python, as a programming language, is now a force to reckon with. Artificial Intelligence and Machine Learning projects are heavily bent toward using Python libraries for their numerically intensive data processing. A language that is widely asked for in job postings, Python has now all but replaced Perl and Shell scripting as the scripting language of choice. As a software developer with significant experience in the C language, picking up syntactical knowledge of new languages is not really a challenge. The real deal is in being able to use the language effectively in building non-trivially complex software systems. I still need to figure out what would be the best course to take here. An open source project would probably be a better way to go as opposed to “Learn Python” books that revolve around writing toy snippets.

I plan on making this blog my extended resume and document my progress on all the above areas, and while at it, hopefully inspire people that peek into my blog to relentlessly pursue their own ambitions.

Here’s to a productive year!