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Achievement: Pull Shark

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Ayesha-Anwar607/README.md

Hi, I'm Ayesha Anwar, a Data Science undergraduate at Khwaja Fareed University (KFUEIT).

I’m passionate about bridging the gap between complex data and intelligent systems. I spend most of my time diving into Machine Learning, Computer Vision, and Distributed Computing. Whether it’s building hybrid recommender systems or scaling models using PySpark and Dask, I love the process of turning raw data into something functional.
💻 Tech Stack: Python, SQL, TensorFlow, and PySpark.
🌱 Learning: Constantly refining my skills in deep learning and Data analysis.

Technical SkillsLanguages: Python, Java, C++, SQL. Frameworks: Scikit-learn, TensorFlow, Keras, PySpark, Dask. Specialties: NLP, Computer Vision, Recommender Systems, and Geospatial Analysis.

Key Projects: Netflix Hybrid Recommender: A movie recommendation engine for 610+ users using TF-IDF and collaborative filtering. Brain Tumor Detection: Distributed deep learning pipeline using VGG16 and PySpark. Spatio-Temporal Crime Analysis: Large-scale urban analytics using parallel computation. "

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  1. Hybrid-Recommender-System Hybrid-Recommender-System Public

    A Full Stack Netflix-style hybrid recommender system — XGBoost ranker over TF-IDF content similarity and item/user collaborative filtering.

    Jupyter Notebook

  2. knn-predictive-analytics knn-predictive-analytics Public

    An end-to-end K-Nearest Neighbors (KNN) implementation showcase. Features dual pipelines for housing price prediction (Regression) and diabetes risk assessment (Classification) with outlier removal…

    Jupyter Notebook

  3. Spatio-Temporal-Crime-Analysis Spatio-Temporal-Crime-Analysis Public

    This spatio-temporal analysis project maps, visualizes, and forecasts regional crime trends. It analyzes historical data across space and time to pinpoint hotspots and optimize police resources.

    Jupyter Notebook

  4. autonomous-revenue-agent autonomous-revenue-agent Public

    An autonomous, event-driven AI agent built with Google's ADK 2.0 and Gemini to monitor enterprise data, predict customer churn, flag overdue invoices, and orchestrate automated recovery actions.

    Python