aadithpm

Thanks for taking the time to share this. I've been mildly interested in a side hustle with the primary goal of picking up new technologies but currently lack the motivation to, after a long job search.

It's interesting to see how you split your time and how much thought goes into all this. A followup question, if you could;

> and most importantly, tools I already feel comfortable with

What do you do in situations where X tool would be 'better' than Y tool, but you're comfortable with Y tool? Do you do a comparison of the time/effort it takes to learn AND use X tool vs. Y?

As a fairly new dev, this is really great information for me. Thanks for posting this.

If you don't mind me asking, roughly how much do you spend (time) on this every week? How much of that is split between development, operations and product or business development?

I'm a graduate student finishing up my Master's @ the University of Houston with a focus on data analytics. Looking for SWE (specifically full-stack/back-end but okay with anything else), data analyst, data engineering positions. I interned at a startup as a full stack dev over the summer (Django, Docker, GCP) and worked for more than a year part-time on campus as a developer (ASP.NET, SQL Server). I've dabbled in various things like data visualization (GLTK, OpenGL), high performance computing (OpenMP, MPI, CUDA), ML (TensorFlow, keras), analytics (Hadoop, SQL, pandas, numpy - can do R but prefer not to) and generally enjoy learning things, trying something new and just solve problems (even those that don't exist ‾\\_(ツ)_/‾

Location: Houston, TX

Remote: Yes

Willing to relocate: Yes

Technologies: Languages - Python, Java, C, C++, Javascript

Web - React, Vue, ASP.NET, Flask, Django

Cloud - AWS (also did analytics w/ Hadoop apart from hosting), GCP, Data - SQL Server, MySQL, MongoDB, Redis,

Other - OpenMP, MPI, CUDA, JUnit, Selenium, Linux

Resume/CV: email me at aadithpm at gmail dot com (or) https://www.linkedin.com/in/aadithpm

Email: aadithpm at gmail dot com

"email addresses are part of the metadata for each individual commit. When those commits are pushed to remote hosting services like GitHub, those email addresses become visible not only to fellow developers, but also to malicious actors aiming to exploit them."

Isn't this overblown a little bit? If it's part of the metadata and it's pushed to a public space, how is it a 'large-scale-exploit'? I might be ignorant of a few things here so would love to be corrected on this.

Any love for Windows?