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Achievement: Pull Shark

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Achievement: Pull Shark

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AyhamAlsuwi/README.md

About Me

I am an Undergraduate Artificial Intelligence Student at the University of Jordan.

My technical progression has evolved from foundational data science, data cleaning, and advanced feature engineering to building robust supervised, unsupervised, and NLP models deployed via production-ready, containerized APIs.

  • Current progress: Transitioning into deep-learning.

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  1. Fraud-job-application-detection-model Fraud-job-application-detection-model Public

    Engineered an end-to-end ML pipeline to detect fraudulent job postings, handling a severe 95/5 class imbalance. Processed messy text and metadata to train a robust classification model, resulting i…

    Jupyter Notebook

  2. IT_ticket_routing_model IT_ticket_routing_model Public

    Built a scikit-learn ML pipeline to automate IT ticket routing. Cleans raw data errors and accurately classifies text to direct requests to the correct department, resulting in FastAPI deployment.

    Jupyter Notebook

  3. king-county-housing-price-prediction king-county-housing-price-prediction Public

    This repository details the data science workflow, feature engineering, and hyperparameter tuning process used to create the final King County Housing Price prediction model, resulting in FastAPI d…

    Jupyter Notebook

  4. USA-used-cars-price-prediction-model USA-used-cars-price-prediction-model Public

    Built a production-ready ML pipeline to predict USA used car auction prices. Features robust data engineering, hyperparameter optimization, and statistical validation, deployed via a FastAPI endpoint.

    Jupyter Notebook

  5. Customer_segmentation_predection Customer_segmentation_predection Public

    Built a multi-class ML pipeline classifying customer segments (A, B, C, D) from demographics. Focused on regularization, identifying data limits, and custom constraints rather than blind accuracy o…

    Jupyter Notebook

  6. Cars-data-cleaning-and-EDA Cars-data-cleaning-and-EDA Public

    This repository contains a Jupyter Notebook for rigorous data cleaning, missing value imputation, advanced feature engineering, and exploratory data analysis (EDA) on a cars marketplace dataset.

    Jupyter Notebook