My 5 Year Machine Learning Journey
To help me understand you fill out this survey (anonymous)
Recently, my content crossed 100,000 views. I’ve been writing for about a year (and really picked up consistency over this summer). I never expected this level of viewership or the positive reception my work has gotten. Therefore, this was quite a surprise to me. It got me thinking about my AI/ML/Tech journey. To celebrate this occasion, I thought I’d write something a lot more personal. I decided to write about the multiple stages of my journey so far.
I’ve had a lot of people reach out to me with their situations asking me for advice about transitioning into these fields from different sectors. I also talked to a lot of students who are looking to break into the field. By detailing the steps I took to get to where I am, and what I learned, hopefully, people will be able to learn from my experiences. My path has been unusual. It is not the usual“get a Master’s/certifications to get an entry-level position into ML and work your way up” story that is recommended these days. I’m not against this approach but not everyone has the capability or desire to go this route. My way is an interesting alternative
Stage 1: Introduction (June 2016-March 2017)
My first real introduction to AI came through some work with Dr. Aditya Abhyankar, Dean of Technology. My mom introduced him to my elder brother, who had a productive experience working at his lab. So he was willing to work with me. He got me to assist a team with the development of intelligent systems. My role was to assist with the debugging, logging, and testing of the bots we wrote. Along with this, I occasionally helped with writing the implementations for certain protocols. I’d tinkered around with some Gridworld projects and robotics at this point, but nothing at this scale. I learned a lot. The most valuable learning I from this experience was simply learning how many little factors we had to consider, and how important evaluating progress at different steps was.
I used Java for this stage. This was the language I had learned in school, and fortunately, it was compatible with the tasks I was given. Since I was still new, the people I was working with would help me out a lot. I was able to learn a lot about programming and problem-solving.
By the end, I had become fairly proficient at my tasks. I would work on and off with different teams to help them with the testing, logging, and report generation aspects of their tasks. I became fairly good at automating pipelines.
Stage 2: Real ML (Septemember 2017- Jan 2018)
I took a bit of a break from Dr. Abhyankar to intern under Phani Bhushan at Anant Computing. He introduced me to software development practices in the industry. It was a pretty interesting experience, and it taught me to write good code and showed me how to collaborate on projects. It was around this time I also started dipping my toes into competitive programming.
Prior to a Hackathon, I came across a Ted Talk about the detection of Parkison’s Disease using Machine Learning. The project was funded by Apple, and they had reached 99% accuracy. The speaker had released a small portion of the dataset online. I decided I would try playing around with this. I was able to build something for the hackathon, but unfortunately, my team lost.
But I kept experimenting with different optimizations and techniques. Eventually, I had a pretty solid proof of concept, which I shared with Dr. Abhyanker. He was intrigued and we worked on formalizing the research. In the end, we ended up with a low-cost algorithm that was robust against noise. The algorithm was patented in 2018. A company licensed the rights to it in 2019.
This was definitely a game-changer. I really started getting into Machine Learning, picked up Python. This patent was also what I used to start conversations and generate interest for leads.
Stage 3: Freelancing (Jun 2018 - March 2020)
Using the patent and internships as a starting point, I started freelancing here and there. I had experience in Coding, Android Development, and AI/ML. I would work with different people on all kinds of projects. This was not full-time, but it allowed me to start coming across the use of technology in different domains. I had become relatively adept at learning different tech stacks and picking up skills on the job. This helped a lot as I worked on projects involving Python, Java, JS (+ HTML/CSS), Kotlin, and C.
This period did not have many “remarkable” achievements for me. But it did help me gain a lot of experience and exposed me to a lot of ideas and challenges. And this allowed me to gain creativity and learn to work out solutions in cases where things weren’t obvious. This skill has helped me a lot coming forward. Many of my managers have praised my ability to be innovative to come up with solutions (like the one above). I believe that stems from my learnings in this stage.
This stage also exposed me to a lot of the assumptions and ideas behind tech. This helped me develop insight into the different protocols and SOPs. For example, in this video, I go over Reinforcement Learning and when you might want to use it.
Stage 4: Hardcore ML (Jun 2020-Present)
In Jun 2020, I worked at Johns Hopkins University. This was by far the hardest project I had worked on yet. We were analyzing the health systems of a State Government to evaluate the impact of different government policies. There were 200+ features, lots of missing data, and tons of noise. It was hard work, but we were ultimately able to do some really good work.
This experience was responsible for teaching me a lot. I was forced to read into multiple techniques, dig through papers and documentation, and test out a lot of ideas. I started writing on Medium (and creating content) as a direct consequence of my work here.
This was also a huge addition to my resume. Having this on my resume allowed me to get work at multiple places, including ICICI Bank, Emory University (I almost went to work there), and ForeOptics (where I work rn). Each experience has further compounded my growth and taught me something interesting. My work has mostly been in Python, and it is at this moment my go-to language.
So, what’s next?
There are a lot of exciting things going forward. My work experience and content have started to attract a lot of attention from people. I’ve reached a point where I can be very confident when approaching interviews. The diversity of my exposure, my ability to learn, and my proven track record allow me to negotiate with people from a position of strength.
My work with ForeOptics ends in December. I am looking at a couple of offers to decide where to go next (If you want to work with me, reach out). Meanwhile, I will continue to learn about ML. Through my content and work experiences, I’ve been able to build up an interesting network of researchers, workers, and other interested parties. Through them, I come across interesting papers, learn about different domains, and can stay updated on recent events in the field. A field like this requires constant evolution, and I’ve really come to enjoy the process.
Hopefully, you were able to learn from my path so far. It has been somewhat unusual, with forays into multiple domains. However, that has also helped me learn how to learn, which has really helped me out so far. And I will continue to keep learning.
If you liked this article, check out my other content. I post regularly on Medium, YouTube, Twitter, and Substack (all linked below). I focus on Artificial Intelligence, Machine Learning, Technology, and Software Development. If you’re preparing for coding interviews check out: Coding Interviews Made Simple.
For one-time support of my work following are my Venmo and Paypal. Any amount is appreciated and helps a lot:
Venmo: https://account.venmo.com/u/FNU-Devansh
Paypal: paypal.me/ISeeThings
Reach out to me
If that article got you interested in reaching out to me, then this section is for you. You can reach out to me on any of the platforms, or check out any of my other content. If you’d like to discuss tutoring, text me on LinkedIn, IG, or Twitter. If you’d like to support my work, using my free Robinhood referral link. We both get a free stock, and there is no risk to you. So not using it is just losing free money.
Check out my other articles on Medium. : https://rb.gy/zn1aiu
My YouTube: https://rb.gy/88iwdd
Reach out to me on LinkedIn. Let’s connect: https://rb.gy/m5ok2y
My Instagram: https://rb.gy/gmvuy9
My Twitter: https://twitter.com/Machine01776819
My Substack: https://codinginterviewsmadesimple.substack.com/
Get a free stock on Robinhood: https://join.robinhood.com/fnud75
