https://github.com/avicenne-ctrl/kaggle-project
Kaggle competitions in order to explore usual ML concepts (classification, regression, NLP, computer vision...)
https://github.com/avicenne-ctrl/kaggle-project
classification computer-vision kaggle-competition kaggle-dataset machine-learning nlp regression-models
Last synced: 12 months ago
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Kaggle competitions in order to explore usual ML concepts (classification, regression, NLP, computer vision...)
- Host: GitHub
- URL: https://github.com/avicenne-ctrl/kaggle-project
- Owner: Avicenne-ctrl
- Created: 2024-11-10T16:58:19.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-12T14:39:21.000Z (over 1 year ago)
- Last Synced: 2025-04-05T18:22:53.042Z (about 1 year ago)
- Topics: classification, computer-vision, kaggle-competition, kaggle-dataset, machine-learning, nlp, regression-models
- Language: Jupyter Notebook
- Homepage:
- Size: 115 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# **KAGGLE-PROJECT**
## **Welcome to the Kaggle Project Repository**
This repository is dedicated to various Kaggle competitions and demonstrate my skills in machine learning with Python. Here, I explore key machine learning concepts, experiment with innovative and original approaches, and demonstrate my skills in tackling diverse data science challenges.
### **Structure of the Repository**
Here are the different thematics :
- Classification
- Regression
- Computer Vision
- Natural Language Processing
- And more to come
- `utilities.py` / `utilities_plot.py` -> redundant function that I've reused in various notebook
Each subfolder corresponds to a different competition theme. Within these folders, you will find a dedicated `README.md` file that explains:
- The objective of the competition
- The unique strategies or methods I used to solve the problem
- Insights gained and key learning points
Whether you're here to learn, explore, or contribute, I hope this repository provides valuable insights into practical machine learning on Kaggle!