Some of my best received posts are
Writing
How to Read a Deep Learning Paper
Who is this for? Practitioners who are looking to level up their game in Deep Learning
Why Do We Need Instructions on How to Read a Deep Learning Paper? Quantity: There are more papers than we can humanly read even within our own niche. For instance, consider EMNLP - which is arguably the most popular Natural Language Processing conference selects more than 2K papers across a variety of topics. And NLP is just one area!
Writing
Character is Net Worth
A useful metaphor to think about character of a person is their financial “net worth”. Like your net worth, this does not mean that you have that much cash to spend. It is a sum total of something.
Net Worth is the Sum Total of the Assets & Liabilities
Character is the Sum Total of the Decisions you Own: Good and Bad
Like your Net Worth can be negative due to a large liability e.
Writing
First 90 Days - Software Engineer Version
Aditya Ankur, asked me:
I know that there is a book for the first 90 days as an executive. Is there something similar for programmers?
I don’t quite know of a book/essay which covers this yet sticks to the question. So I am writing one for him.
The First 90 Days for a New Engineer I expect each step to take roughly between 10 and 30 days, depending on the pace of your project + size of the team.
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Building a Data Science Team at a Startup
Hello!
If we are meeting for the first time, a short version of my story so far: After doing research engineering for almost 4 years across startups and a BigCo, I joined as an early machine learning engineer at Verloop.io - a B2B startup that makes customer support automation SaaS in 2019. I was there till April 2021.
We were directly responsible for most Natural Language Processing needs within the business.
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Verloop NLP Interview Prep Guide
Update, September 2021: This guide is a little outdated, but not obsolete. I no longer work at Verloop.io.
Preparation Guide I’ve been an early Machine Learning Engineer at Verloop.io for almost 1.5 years, primarily working on NLP problems and now more in an Engineering Manager-ish role.
This is the guide which I sometimes send to our candidates after they submit the Programming Challenge. If a candidate has relevant open source code sample, specially to other repositories we may choose to waive off the Programming Challenge completely.
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Talent Cooling
Talent Cooling Kills Startup Growth Evaporative Cooling of talent occurs when the most high-value contributors to a community realize that the community is no longer serving their needs anymore and, therefore, leave.
Then something remarkably interesting happens:
When that happens, it drops the general quality of the community down such that the next most high-value contributors now find the community underwhelming. Each layer of disappearances slowly reduces the average quality of the group until such a point that you reach the people who are so unskilled and unaware of it that they’re unable to tell that they’re part of a mediocre group.
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Shreyas Karanth: Moving from SW Engg to Product
Shreyas Karanth is a Product Manager at Soroco. Soroco is a Medium-sized Enterprise-focussed B2B Automation company. Before Product Management, Shreyas was the fastest growing engineer - going from a fresh grad to a Technical Lead within 3 years of graduation.
This is also when I worked with him, during his engineering days. Here, I asked a bunch of questions why he moved to Product Management, what excites him and what he considers as Product Management work at Soroco.
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Standing Out at Work
In my short career, I’ve seen some amazing young people stand out at work.
Here is what they did, organized by 5 themes:
Unlock Knowledge
Automate Boring Stuff
Write Widely
Solve Open Problems
Outside-Visible Work
Unlock Knowledge Expertise and know-how stay trapped in emails, docs and codebases. Unlock this for everyone else.
Get your Star Salesman on an internal podcast to spill their secrets. Do email interviews with your tech leaders and PMs.
Writing
Fail Resume
A fail resume is, as its name suggests, a list of rejections and setbacks.
This concept originated in academia, but can be applied to improve one’s career, resilience, and approach to challenges in any walk of life.
I’ve organized my setbacks by year (starting with 2016), and what constitutes a “failure” (or fail) here is based solely on my own judgement. It’s important to not only list the failures, but also learn from them, so I will add reflections to some of them (in progress).