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Achievements

Achievement: Pull SharkAchievement: YOLOAchievement: Quickdraw

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SaribAzim/README.md

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Research Projects

Neural Network Calibration Study

Repo

Post-hoc calibration analysis of ResNet-50 on CIFAR-10. Measured systematic overconfidence using ECE and MCE. Applied temperature scaling — a single scalar T — to reduce ECE by 67% without retraining.

Key finding: High top-1 accuracy and good calibration are independent properties. Most models only optimise for one.

PyTorch Calibration ResNet-50 Temperature Scaling

Based on Guo et al. (2017), ICML

CNN vs ViT Interpretability Study

Repo

Comparative saliency analysis across ResNet-50, EfficientNet-B0, and ViT-B/16 on ImageNette. Implemented Grad-CAM for CNNs and Grad-CAM with patch reshape transform for ViT.

Key finding: CNNs focus on local discriminative patches. ViT attends globally — even when all three models agree on the correct label.

PyTorch Grad-CAM ViT Interpretability

Based on Selvaraju et al. (2017), ICCV

Attention-Based BiLSTM — Fake News Detection

Repo

Sequence classification using bidirectional LSTM with attention for multilingual fake news detection.

PyTorch NLP BiLSTM Attention

Auto-Complete System — NLP

Repo

Language model-based autocomplete system built on neural sequence modeling approaches.

NLP Language Modeling TypeScript

Technical Stack

Python PyTorch NumPy Git TypeScript Linux

Spotify

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LinkedIn GitHub

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  1. Attention-Based-BiLSTM-for-Multilingual-Fake-News-Detection Attention-Based-BiLSTM-for-Multilingual-Fake-News-Detection Public

    Python

  2. Auto-Complete-System-NLP- Auto-Complete-System-NLP- Public

    TypeScript

  3. CNN-VIT-Interpretability-Study-with-Grad-CAM-and-Reshape-Transform- CNN-VIT-Interpretability-Study-with-Grad-CAM-and-Reshape-Transform- Public

    Interpretability study comparing how ResNet-50, EfficientNet-B0, and ViT-B/16 visually reason about images — using Grad-CAM for CNNs and Grad-CAM with reshape transform for ViT, across 10 ImageNett…

    Python

  4. Neural-Network-Calibration Neural-Network-Calibration Public

    Post-hoc calibration study using temperature scaling on CIFAR-10 — ECE reduced 67% with a single learned parameter. Based on Guo et al. (2017)

    Python

  5. SaadAhmed29/BioFusion-AI SaadAhmed29/BioFusion-AI Public

    Cross-modal breast cancer diagnostic tool combining CNNs and clinical risk factors to enhance radiologist decision-making. 92% accuracy with ensemble learning.

    Python