This repo mirrors my public Kaggle notebooks and keeps them in one clean, versioned place.
What you will find here:
- End to end EDA and storytelling notebooks
- ML baselines to strong solutions (tabular + competitions)
- Deep Learning projects in Computer Vision and NLP
- LLM experiments and practical inference techniques
Main hub (all notebooks):
- Data Analysis and EDA
- Computer Vision
- NLP
- LLM and Transformers
- Time Series and Finance
- Machine Learning and Tabular
Tip: For the newest work first, open the Kaggle link above and sort by “Updated”.
Data Analysis, EDA, Machine Learning, Deep Learning, Computer Vision, NLP, CNN, RNN, Transformers, LLM, Fine-tuning, Time Series, Tabular Data, Image Classification, Kaggle Competition
Planned next:
- Optuna Tuning
- Object Detection
Each row has a Kaggle link and the matching notebook file in this repo.
| Notebook | Kaggle | GitHub |
|---|---|---|
| Kaggle Mastery: Summarize Kaggle solution write up | https://www.kaggle.com/code/ibrahimqasimi/kaggle-mastery-summarize-kaggle-solution-write-up | Open |
| Steering an LLM at inference (SAE feature vectors) | https://www.kaggle.com/code/ibrahimqasimi/steering-an-llm-at-inference-sae-feature-vectors | Open |
| Notebook | Kaggle | GitHub |
|---|---|---|
| Amazon Stocks Data Analysis | https://www.kaggle.com/code/ibrahimqasimi/amazon-stocks-data-analysis | Open |
| NVIDIA Multi Timeframe Stock Analysis 1999 to 2025 | https://www.kaggle.com/code/ibrahimqasimi/nvidia-multi-timeframe-stock-analysis-1999-2025 | Open |
| Notebook | Kaggle | GitHub |
|---|---|---|
| FINAL Heart Disease Prediction | https://www.kaggle.com/code/ibrahimqasimi/final-heart-disease-prediction-me | Open |
A lot of this work was not done in isolation.
Across multiple notebooks, I have worked with different teammates and contributors. You can see this directly on Kaggle in the notebook “Authors” and “Editors” section. In some projects I am the main author, in others I contributed as an editor or co author.
Thanks to everyone who collaborated with me, reviewed ideas, improved code, shared feedback, or helped refine the final notebook.
If you were a collaborator and I missed your name here, message me and I will add you properly.
If these notebooks help you, please star the repo. It helps more learners discover the work.