Notes and learnings from the GrandMaster Panel at H2OWorld

You can find me on Twitter @bhutanisanyam1

Note: This post first appeared on the H2O.ai blog

Personally, I’m a firm believer and fan of Kaggle and definitely look at it as the home of Data Science. Kaggle Grandmasters are the heroes of Kaggle or definitely mine. I’ve been on a pursuit to depict and understand their journey into the field also if they’re still humans or have passed onto an alternate reality (not still sure about that one).

H2O World event recently had the biggest Kaggle Grandmaster Panel. This post will share my takeaways from the panel discussions along with…


A quick recap of a community taught ML Engineer’s journey.

Milestones and a Full-time Job

15th of October, 2019 marks a special milestone, actually quite a few milestones. So I considered sharing it in the form a blog post, on a publication that has been home to all of my posts :) (Note: This was originally posted in HackerNoon)

The online community has been too kind to me and these blog posts have been a method for me to celebrate any achievements big or small with the amazing people that I got know via slack groups: KaggleNoobs, ODS.AI, TWiMLAI, Data Science Network, the fast.ai …


An overview of Data Science Network’s largest community event

Full House for the event

This weekend, the Data Science Network Team hosted one of the largest community events and one of India’s largest Kaggle Days Meetup.

I’d also like to point out that like all of the DSNet and Kaggle related community events, this event was also free of cost-Thanks to our venue sponsor Manipal ProLearn.

What is Kaggle Days Meetup?

You might be familiar with the KaggleDays which is an event hosted by Kaggle and Logic AI in the form of an offline-global scale Kaggle event.

KaggleDays Meetup: is the community-driven, meetup version of KaggleDays.

This means a few things:

  • A meetup with a Kaggle theme.
  • Different Levels…

Re-boot of “Interview with Machine Learning Heroes” and collection of best pieces of advice

During the past few months, I was really lucky to have interviewed Top Kagglers, Researchers and Practitioners. These interviews were released in a blog format and each week and all of the ML heroes were kind enough to share many amazing words for beginners, share about their journey into the field.

In this post, I’m super excited to announce Chai Time Data Science:

Chai Time Data Science is the reboot of Machine Learning Interviews, I’ve been working on this project during the past 3 months and I’m super happy to share that the first episode will be released on…


Re-boot of “Interview with Machine Learning Heroes” and collection of best pieces of advice

During the past few months, I was really lucky to have interviewed Top Kagglers, Researchers and Practitioners. These interviews were released in a blog format and each week and all of the ML heroes were kind enough to share many amazing words for beginners, share about their journey into the field.

In this post, I’m super excited to announce Chai Time Data Science:

Chai Time Data Science is the reboot of Machine Learning Interviews, I’ve been working on this project during the past 3 months and I’m super happy to share that the first episode will be released on…


A write-up of my first kaggle competition experience

Photo by Victoire Joncheray on Unsplash

During my Initial planning on My Self-Taught Machine Learning journey this year, I had pledged to make into Top 25% for any 2 (Live) Kaggle competitions.

This is a write up of how Team “rm-rf /” made it to the Top 30% in our First kaggle competition ever: The “Quick, Draw! Doodle Recognition Challenge” by Google AI Team, hosted on kaggle.

Special Mention: Team “rm-rf /” was a two-member team consisting of my Business partner and friend Rishi Bhalodia and myself.

Experience

Picture this: A race that goes on for three months. There is no finish line, there are high-scores. …


Meta Article with links to all the interviews with my Machine Learning Heroes: Practitioners, Researchers and Kagglers.

During the past few months, I’ve spent time interviewing great practitioners, researchers and kagglers.

This post serves as an index or Meta-Article with a link to all of the interviews that I’ve conducted. I’ll keep updating this post as the interviews happen.

Photo by Michael Browning on Unsplash

About the Series:

I have very recently started making some progress with my Self-Taught Machine Learning Journey. But to be honest, it wouldn’t be possible at all without the amazing community online and the great people that have helped me.

In this Series of Blog Posts, I talk with People that have really inspired me and whom I…


A 1-year update on my “Self-Taught” Machine Learning Path

This blog post is to share with you an update about my “Machine Learning Journey”, 1 year down the path.

A few of my readers have been kind enough to also reach out and ask if the interview series has ended or the reason for not putting out more blog posts recently. This blog post will (hopefully) also share the reason for the same:

Earlier this year, I was invited by Google to interview for the 1 year Google AI Residency Program: My application was considered for the “final round” of interviews: The “onsite interviews”, the preparation process had kept…


Hi Everyone,

Thank you so much for subscribing to and reading to init27 (Now, Neuroascent.ml) publication.

I’m very grateful to all that read our content, left feedback and even contributed to the publication.

I’m super excited to announce the (official) kick-off for DSNet!

You might be familiar with DSNet from the meetups hosted by Aakash N S and Siddhant Ujjain.

With DSNet, we hope to expand the online publication as well as foster an online community.

We will be shutting down init27 labs and moving all content to DSNet https://medium.com/dsnet

Thanks for your feedbacks from earlier. Here is what we…


An example based walkthrough of applying image augmentation using the fastai library

Photo by Thomas Willmott on Unsplash

You can also find the executable code of this blog in this kaggle kernel .

For more details on the fastai course, or library: please checkout the course website and library docs.

Introduction to the writeup

The aim of this writeup is to give you a walkthrough of all of the image augmentations in fastai. I’ll start by introducing data augmentation followed by image augmentation.

Then we’ll make a case of why fastai defaults “just works”.

Next, we’ll look at a few real-world use-cases where this transforms will be super useful:

  • Building a SOTA neighborhood swimming pool detector
  • Building a medical image OCR
  • Building…

Sanyam Bhutani

Machine Learning Engineer and AI Content Creator at H2O.ai, Fast.ai Fellow, Kaggle x3 Expert (Ranked in Top 1%), Twitter: https://twitter.com/bhutanisanyam1

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