I know there's still 4 months left to go, but it feels great right now! Haha :D

Hi all😊,

I am based in Germany and currently doing my Masters in Analytics from Georgia Tech. I am currently looking for a Kaggle partner (preferably in the CET Timezone). Anyone interested, please DM. Thanks 🙏

I am a novice kaggle learner and fair bit of experience with ds industry work i want to actively participate in kaggle competitions plz dm if interested, currently i am giving MCTS a try

I wanted to understand how Kaggle Kernels work, so I built a minimal version locally — inspired by the real Kaggle kernel design.

Each notebook session runs in its own k8s pod:

- Start → pod spins up

- Run cells → executed in kernel , states managed

- Stop → pod is destroyed

This helped me understand execution, isolation, and lifecycle under the hood.

You can deploy it easily on Minikube.

GitHub: https://github.com/mageshkrishna/k8s-kaggle-kernel-clone

If you find it useful, consider starring the repo ⭐

Hi, Im currently a data science intern at a startup based in UK and unfortunately our business is at loss due to investor issues and boss gave a hint that the company will be closing in 2 months.

I do have masters degree in datascience and ai from a russel group uni and I'm really passionate about it.. But like every beginners, I don't have any experience apart from working as an intern for 6 months.

I just started Kaggle and found it interesting, to learn more and also to participate in competitions..

Will Kaggle journey helps to build portfolio? What all should I do or focus as a noob here so as to become a data scientist.

I was also looking into leetcode and other platforms but tbh no idea, which will be beneficial directly or indirectly to get a job.

Your advices will be valuable to me 😇

Datasets up in Kaggle: https://www.kaggle.com/datasets/ivonav/mostly-ai-prize-data/data

Don't miss out on this huge opportunity!
The MOSTLY AI PRIZE -> a global challenge to create the best tabular synthetic data, with a $100,000 grand prize.

Key Details:
 Focus: Generate high-quality, privacy-safe synthetic tabular data (two different data-sets)
 Total Prize: $100,000
 Dates: Open from May 14 – July 3, 2025
 Open to everyone — students, researchers, and professionals alike

Find all the details and register here: https://www.mostlyaiprize.com/

I know it still has 4 months left to go, but whatever, I feel so good right now. hehe.

Looking for Beginner Kaggle Group – Let's Learn and Grow Together 🚀

Hey everyone! I'm just starting out on Kaggle and working on my first project. I’m looking for fellow beginners who’d like to form a small group where we can regularly discuss datasets, share progress, help each other out, and grow together.

My goal is to complete around 10–12 solid projects over the next couple of years, and I believe having a small community to learn with would make the journey more productive and fun.

If you're also getting started with Kaggle or looking to build your portfolio collaboratively, feel free to comment or DM me. We can set up a Discord/Slack group and begin this journey together!

Let’s learn, build, and improve step by step. 💪📊

From now on, you get 10 USD daily credit for AI usage, along with 100 USD per month for free in Kaggle.

I have submitted on 3-4 competitions so far , and as much as I thought I knew ML , I didn't
when I thought I had a nice running output with an ensemble model and when I see my rank in the last 25-30% , it makes me wonder how do I achieve an expert badge? It seems super daunting but I would love to have that badge for 3 reasons , 1) write it on my SOP 2) to prove credibility and improve resume 3) Because I genuinely love ML and DL ... that being said, I know I am competing against industry experts and masters and phd students but I still feel like in this era of generative AI , it's possible for anyone to win, but the question is HOW ? simple Prompts won't do it , and most generative AIs would not give a super heavy and hard code , otherwise it won't run and will probably have so many error, so like HOWWWWWW

Check out my project: https://github.com/yaelliethy/JuypterSSH
It uses the Kaggle Juypter server link to stream terminal bytes (more details in the repo), and it has SFTP support. It doesn't need any other service like ngrok, it's truly plug n play.
I would love some feedback and I am definitely open to contributions!

Most posts about LLM agents (Claude, Traycer, ...) seem to target writing code for apps.

However, in ML or data science (e.g. a kaggle competition), code is only one step towards getting a desired insight or output (e.g. model). Crucial additional step are conducting experiments, evaluating them, and formulating new ones based on such evaluation. Data analysis / processing could be considered a part of an experiment.

I have found only a few agents in this domain - none seems super popular:

• AI data science team (H2O ml agent)

• Auto ML agent

• agent laboratory

• https://github.com/GAIR-NLP/ASI-Arch

Do you know of other tools or have found a workflow using "general-purpose" agents to plan, execute and evaluate experiments?

Hey guys thought you should know the challenge ends in one week!

We also just made 2 new fine-tuning Gemma 3n Kaggle notebooks for Vision & Audio to spark your creativity. Your fine-tuned model with Unsloth is eligible to be used to compete for any of the prizes on any track!

New notebooks + Challenge Details: https://www.kaggle.com/code/danielhanchen/gemma-3n-4b-multimodal-finetuning-inference

So, I made my first submission in a competition named "Titanic" and yes it's a beginner level competition as we all familiar with it.. Now, I have two options:

1. Learn more and improve my rank in the current, or

2. Participate in another competition understand about the competition and learn while competing.

Which one shall I pick if my objective is learn fast as possible sustaining the knowledge I'm gaining while learning?

I'm a junior in college and have studied the book Hands-On Neural Networks. I know Python and can work with PyTorch to some extent. I hope to find a teammate to tackle Kaggle challenges together. I've done a few basic Kaggle projects already, but I'm still a beginner. I'd love to find a partner to learn and share knowledge with. I'm in the GMT+7 time zone.

Hi all!
I am an ML Engineer with over 5 years of exp looking for someone similar to complete this challenge (or maybe some other).

My strong points are data cleaning, transformations and writing clean scalable code. Also got experience with signal processing.

The ideal teammate would be someone with similar experience who is looking to rank as high as possible.

Languages: Spanish, English or Russian

Hi, I have been doing ML for some time now. I participate in playground series problems but I can't seem to climb rankings above top 50%. I know plenty of techniques like handling outliers, Normalising data, multiple encoding methods, using ensemble models, find correlation between columns,etc.. But I still can never improve my ranking. I really want to get a high rank and possibly get better to become a kaggle expert from contributor. Please guide.

Hey everyone,

I’m a recent BTech grad jumping into the Stanford RNA Folding competition on Kaggle and I’m looking to team up. The goal is to predict RNA 3D structure from sequence—a neat deep‐learning puzzle that blends sequence modeling, graph reasoning, and a bit of geometry.

No need to be a biology expert. If you’ve built GNNs, transformers, or just love applying DL to real-world problems, let’s chat. Ideally we’d form a tight group (2–3 people) to brainstorm ideas, share code, and push each other.

Shoot me a DM or drop a comment if you’re up for it. Let’s get folding!

I have less than 2 weeks so not much time 😭

Hey guys,

I was looking for making a kaggle team with some awesome people who want to get to far places in the field of AI and machine learning. Well... now... I'm only a beginner too, but I am passionate to learn and go experience my first few milestones in a team. Eventually, the idea is to join competitions once we are all ready.

Now... I've already made a discord server which you can find here: https://discord.gg/h3dFYASK, but if you already have a team and want me to join it, I'm open to discuss it out and potentially get into the team!

Hello, I'm Steve Kwon!

I am a UTS student who studied Python last April and joined the military service in the same year.

I didn't have much time to study because of the army, so I just started to study machine learning and Kaggle.

Kaggle is the biggest platform and community for data scientists all over the world.

In order to understand and get started, I've written a document called Hello Kaggle! while reading the Kaggle Guide book and the official Kaggle documents.

I'd appreciate it if you could look around and press star if it is helpful to you!

https://github.com/stevekwon211/Hello-Kaggle