This series of articles will contain my journey and what I learned every day while participating in Kaggle's 30DaysOfML Challenge.
If you would like to follow my journey through this challenge, be sure to follow this series. I would be attaching the resources links at the end of the article.
Contents
✅ Abstract
🌟 What I learned
🔚 Conclusion
📒 Notebook and Resource Links
😎 Let's Connect!!
✅ Abstract
This part is just me talking about myself😆😆 and why I took up the challenge, so you can skip ahead, you won't miss anything important! but I do hope you give it a read.😊😊
I have been working in Data Science for almost 2 years now! Completed a lot of tutorials built 50+ projects of my own, uncountable notebooks, etc... What I didn't do was being active on Kaggle. It's not that I never thought of being active there. Then I received the mail for 30 days of ML challenge and it hit the mark with 1st line.
The specific line: the challenge is designed to help you grow from non-coder to Kaggle competitor in 30 days
While I consider myself a good coder😎😎(I didn't say excellent), This time I wanted to relearn some stuff from the ground again. This challenge was offering all of that!!
🌟 What I learned
The mail I received on the 1st day contained very clear instructions, a roadmap for this week. I have shared the official notebook by Alexis Cook at the end.
These are some of the things I learned
- understand your Kaggle profile
- how Kaggle's rankings work - Progression System
- moving your ranking from Novice to Contributor (This actually happened)
- how to participate in a competition
- participating in Titanic Kaggle Competition
- My First Submission in a competition - (Thanks to all the clear instructions)
- Comments and upvotes for the rank upgrade
- There you go!! you are a competitor now
These are all the things I got to learn on the first day. It took me around 30 minutes, reading and completing everything with ease. very excited to see what I would get today!!
🔚 Conclusion
The way they are taking this challenge is just amazing. I was provided with very clear instructions and doing the things the practical way it just amazing. Again, I think this is truly a valuable course for people who are non-coders and actually interested in machine learning. You all just need a computer/laptop with internet access and a browser.
This week's plans are to solely focus on Python Learning.
📒 Notebook and Resource Links
The author and instructor for the challenge - Alexis Coal
The official notebook for day 1 - kaggle.com/alexisbcook/getting-started-with..