Azizullah Naik

Azizullah Naik

@azizullahnaik

ML Developer | Computer Vision | NLP | Python Developer | Data Science

Innovative Design Express Karachi, Pakistan
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Language Breakdown

Lines of code distribution across 8 owned repositories

4.7M Total LOC
Jupyter Notebook
4,733,167 lines
100.0%
N/A
I

I-Shaped Developer

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Specialist — deep expertise in Jupyter Notebook

Jupyter Notebook

Collaboration Network

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Azizullah Naik
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Repos

8

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Growth

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Coding Streak

Contribution activity over the past year

1 day
39
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Top Repositories

AI-StoryTeller
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Jupyter Notebook
scarf-detection

A MobileNetV2 model was successfully fine-tuned using Transfer Learning on the Scarf Detection Dataset to classify images. Achieving high validation and test accuracy (e.g., 94.07%), the model demonstrates strong generalization capability, confirming its readiness for deployment in the interactive image classification system.

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azizullahnaik
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Aircraft-Classification-With-PyTorch-Agentic-AI

A CNN was trained on a dataset to detect military aircraft, achieving 100% training accuracy. This result suggests overfitting, so the next step is to test the model on unseen images to verify its actual performance.

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Jupyter Notebook
road-segmentation-using-u-net-architecture

This project uses a U-Net model to segment roads in satellite images from the DeepGlobe dataset. Data is loaded directly from Kaggle, preprocessed, and resized. The model is evaluated using Dice and IoU scores with prediction visualizations. It's a complete Kaggle-ready project, extendable with augmentation or submission generation.

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Disease-Detection-

Uses symptom presence as features to predict likely diseases. Includes data preprocessing, binary encoding, and top-5 disease recommendations using a trained Random Forest classifier. Built with Python and Scikit-learn.

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Movie-recommendation-engine

Content-based Movie Recommendation Engine using genres, cast, and overview features. Includes data preprocessing, EDA, and similarity-based recommendations using cosine similarity. Built with Python and Scikit-learn

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Jupyter Notebook
House-price-prediction

Machine learning model to predict house prices using features like size, location, and number of rooms. Includes data preprocessing, EDA, model training (Linear Regression, Random Forest, XGBoost), and evaluation.

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Open Source Impact

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