Why I am relearning math now
Sometimes, some things are not meant to be… until they are. Over the last year and a half, I’ve picked up two life skills — exercising and writing — that I have been avoiding for over a decade now.
Exercise: Almost a decade ago, I used to cycle over 120 kilometers each week. But then, I started my first business and since then my fitness has been on a downward trend. Twelve months ago, I started learning how to work out. I started with something as simple as jumping jacks and 500 gram weights and overtime built up my cardio and strength capacity. I will write more on this journey later.
Writing: I do not see myself as a professional writer, but I’ve always written extensively to bring clarity to my thinking. Later, as a Knight Fellow with ICFJ, I co-authored reports with professional journalists for wider consumption:
- WhatsApp funded project Checkpoint
- Two research reports on the state of development journalism in India for BMGF
- A working paper on how cognition makes misinformation more persuasive on WhatsApp that I presented at Poynter’s GlobalFact 7 conference
That’s when I realized how different (and nuanced) it is to write for public consumption and the level of communication skills that journalists command.
Over the last year and a half, encouraged and mentored by my bosses at TOI, I am finally blogging at https://next.timesofindia.com and https://tech.timesinternet.in.
Today, I want to plant the flag on a third life skill — math. It is a project that I envisage will last at least for 12 months. Like how I started off with jumping jacks, I will start off with basics and often awkwardly and work myself up the value chain.
What not: Just as I did not aspire to become an athlete or a writer, with math too, I do not aspire to be a mathematician, statistician, data journalist, or data scientist. I just want to add the ability to earnestly and meaningfully collaborate with mathematicians, statisticians, data journalists, or data scientists.
What: I want to build a working intuition towards math, mathematical or statistical thinking, symbols and terms used, graphs and mathematical diagrams. I will focus on linear algebra, probability, and statistics.
Why: Coincidentally, I’ve always worked in domains that are adjacent to math:
- In 2005, my year-old project at University was to predict movement in stock markets using Neural Networks in MatLab.
- In 2013, I started an information design studio which focused on custom-building data visualizations. As we all know, geometry is all math. Additionally, during this time, we often worked with data analysts and data scientists from the insurance, healthcare analytics, and FMCG domain.
- In 2017, as an ICFJ Knight Fellow, I started working with and training data journalists in the media space.
- Somewhere in the middle, my friend Deepan — a math and trading/investments whiz — and I considered starting up in the space of algorithmic trading.
- Now at TOI, I have worked on data-heavy projects with Covid-19 and Elections data and now am product managing machine learning projects.
Should I bother? My data journalism and machine learning colleagues have always been fairly patient and generous enough to answer my embarrassingly simple math questions and bear my lack of nuance of why this and not that. Yet, I feel one should have a decent grounding of basics to collaborate more productively.
Didn’t I learn anything in school and college? Frankly, I lost interest in math because I never saw any utility for it. It is only now — after years of working — that I see it everywhere.
Inspiration: While I have been thinking about learning math for years now. I recently read this blog from Samarth Bansal and it pushed my decision past the line. 🙏 Below are some lines from his post that resonated with me:
If I am told that the unemployment went up from 4.2% to 4.9% — how do I assess if this rise is statistically significant or not? What if the change is simply a reflection of random fluctuation? How should I think about the threshold? At the moment, I can’t answer these questions with mathematical precision.
Statistical inference lies at the heart of scientific inquiry and not knowing its fundamentals means I can not fully participate in understanding what’s really going on.
Using fancy tools like neural nets, boosting and support vector machines without understanding basic statistics is like doing brain surgery before knowing how to use band-aid.
The one we are living right now was not “meant to be” — it is just one of the infinite paths the world could have taken.
How do I plan to avoid the boring parts? I still do not see value in learning how to calculate things so I will learn a bit of Python to do the calculations there.
Where do we begin? As stated earlier, I will start from absolute basics and then build up with time. I am starting with Linear Algebra.
How will I create time? I work full-time at TOI and also have a six-year old daughter.
Creating time for new pursuits is always a challenge. One way we have addressed this so far is by interweaving our family time with various projects:
- Drawing: In 2018, my daughter and I learned doodling together.
- Exercise: My daughter started training with me and we go on long walks on weekends.
- Reading: We taught our daughter to enjoy reading early on and so my wife and daughter have their reading time together. I do my writing during this time.
Adding math in our family time will be a unique challenge. I will figure this out with time. I will keep posting more on this.
