I don't urge you to sponsor, if you feel like supporting my work, or have used it or just the OSS community in general, feel free to sponsor!

About Me

I am a high school student from Mumbai, India. I love working with Machine Learning, especially Computer Vision and Kubernetes (and a Kubernetes org member) but you will also find me working with Android. I am an active contributor to multiple open-source projects like TensorFlow, KubeFlow, and Kubernetes. I also love building open-source projects (usually related to Kubernetes and Machine Learning) and some of which have been #1 trending on GitHub.

I have consequently won top contributor awards 🏆 or similar from TensorFlow, freeCodeCamp, PapersWithCode, Google DevLibrary, and more.

Seeing my work at a rather young age, I was invited to speak at 2 TEDx and 1 TED-Ed events, I have represented my country in multiple international hackathons and won a few too and I’m also a Linux Foundation Dan Kohn Scholar. Most of the time you will find me working on a new ML research idea and I have a couple of published papers as well.

Why a sponsorship matters to me?

At the moment, all my open-source contributions and projects are out of passion and free time and I use the awesome GitHub Student Developer Pack. This often not enough for some of the open-source projects I create, one such was when I got too much traffic on a project I built 😄 but that ended up exhausting my GitHub LFS and drained my Azure Student credits 😢 in a matter of a few hours!

Being a student, the machine I use 💻 or the cloud credits I frequently use, or the TPU resources I use are all from winning hackathons or grants.

A sponsorship could go a long way for me to better the quality of open-source projects I have been up to.

How will I use sponsorship?

Following the awesome ideals of freeCodeCamp, each dollar you donate will be matched by me. The sponsorship goes entirely towards my projects, especially on things like LFS bandwidth on GitHub, Action Minutes on GitHub, and cloud credits for hosting projects.

statistics

Skewness and Kurtosis – Positively Skewed and Negatively Skewed Distributions in Statistics Explained