Silver BlogGold BlogJourney to Machine Learning – 100 Days of ML Code

A personal account from Machine Learning enthusiast Avik Jain on his experiences of #100DaysOfMLCode, a challenge that encourages beginners to code and study machine learning for at least an hour, every day for 100 days.

By Avik Jain

Would you let an Artificial Intelligence make decisions on for behalf? — If Yes, then to what extent, maybe your life depends on it. With all the talk about AI and calls for its regulation (apparently AI will kill us all someday,) I’ve been thinking about under what circumstances we might take away the decision making from the machines (call it AI). But still we use them to our advantage (as much as we can) — that’s not as crazy as it sounds, because humanity has been doing that for years already. It’s everywhere, and there is no hiding from the fact that it is here to stay.

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From the incredibly-friendly voice of Apple’s personal assistant, Siri, to movies like Ex-Machina, Al has always excited me more than anything else. I don’t know about you, but the very idea that Netflix can actually predict a recommendation list of movies based on your reaction to a previously seen movie sounds fascinating to me.

Then one day out of nowhere I come across a video on YouTube by Siraj Raval, in which he talked about something called #100DaysOfMLCode Challenge. It means coding and studying machine learning for at least an hour, every day for the next 100 days. I highly recommend to check out the video.


It was just the right type of motivation that I needed to start learning in depth about something I’ve always cared about. So I took this challenge and started learning about machine learning.

Beginning with the most basic algorithms and implementing them in the Python language.

Just so that I have a good log for everything that I’ve learned, I created a repository on GitHub. I will highly recommend you to do the same. As I continually learned new things about ML, I’ve also updated the repository with the code for implementing ML algorithms along with some info-graphics for better understanding.

Some of the Infographics

The response that I’ve received for the repository is very overwhelming, to say the least, I didn’t expect this. People have been supporting me from every corner of Social Media, and it most certainly humbles me, and I would like to take this opportunity to say thanks to everyone who has given their precious time to me.


Checkout My Repository

Numbers are not relevant here, because I didn’t do this for fame or any popularity. I did it because I wanted to, I care about it, and I believe that I can make a difference.

K — Nearest Neighbor Info graphic

With all that said, I believe that I’m only learning right now, and in this fast-changing and an ever-evolving world, I think that you never actually finish learning. It’s just a big learning curve. The destination is not here yet, I am not even close, to be completely honest. But I do know that my path is right, and my mind is focused on achieving what I aspire to do. So I would like to challenge everyone reading this right now to come and join me on this journey, take the #100DaysOfMlCode challenge and start working every day.

And if you don’t have an interest in this field of AI, that’s not a problem or an excuse, find something which you care about, something which doesn’t feel like work, something to which you can dedicate your entire life. Les Brown once said,

“To achieve anything worthwhile in your life, you got to be hungry.”

Be hungry for success, follow your dreams and watch them become your reality.

Start this journey with me, and perhaps maybe one day we’ll together get to a point where we can live our dreams, and you knows to where beyond.

Follow My Work on #100DaysOfMLCode From below links —

Github | LinkedIn | Twitter | Website

Original. Reposted with permission.

Bio: Avik Jain is a Machine Learning and Cloud Computing Enthusiast, skilled in C , C++,Python, Cloud Computing, Adobe Creative Cloud. Currently pursuing Bachelor of Technology (B.Tech.) focused in Computer Engineering with Specialization in Cloud Computing from University of petroleum and energy studies and actively looking for internships.