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Achievement: Pull Shark

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Achievement: Pull Shark

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DevDizzle/README.md

About Me

I am a machine learning engineer with a focus on developing impactful AI solutions across healthcare, logistics, and personal finance. My expertise lies in leveraging advanced machine learning techniques, optimization algorithms, and cloud technologies to solve real-world problems.

Technical Skills

  • Machine Learning Frameworks: Proficient in TensorFlow, PyTorch, and Scikit-learn.
  • Cloud Platforms: Skilled in Google Cloud Technologies, including Vertex AI and Dataflow (Apache Beam).
  • AI Applications: Experienced in data preprocessing, model training, evaluation, and deployment at scale.

Notable Projects

  • Skin Lesion Classification: Developed a classifier using Vertex AI AutoML, achieving 94% precision and recall in identifying malignant lesions.
  • Route Optimization App: Built a web application to solve Vehicle Route Problems (VRP), simplifying complex logistics challenges.
  • RobotX 2024 USV Competition: Contributed to Team Owltonomous by developing an object detection model using YOLO.

Research and Writing

Interests and Collaboration

I am passionate about:

  • AI for Good: Advancing AI to maintain America’s leadership in innovation and technology.
  • Optimization Algorithms: Methods to improve decision-making processes.
  • Academic Collaboration: Excited to join the ISCAAS lab at FAU and contribute to ongoing research.

Hobbies

In my free time, I enjoy exploring philosophy, building web applications, and fostering a balance between career ambitions and raising my family.

Pinned Loading

  1. linear-programing-assest-allocation linear-programing-assest-allocation Public

    This notebook performs portfolio optimization for a selection of Exchange-Traded Funds (ETFs) with the goal of minimizing investment risk while ensuring a minimum annual return.

    Jupyter Notebook 2

  2. node-pruning-research node-pruning-research Public

    Project exploring the impact of node pruning on CNN performance metrics within a stratified k-fold cross-validation framework. Focuses on optimizing recall for medical imaging tasks while analyzing…

    Jupyter Notebook 1

  3. ridge-logistic-regression ridge-logistic-regression Public

    Exploration of Ridge (L2) regularization effects in multiclass logistic regression, analyzing coefficients, cross-validation error, and predictions for optimal tuning.

    Jupyter Notebook 1

  4. travel-recommender travel-recommender Public

    A simple, dynamic travel recommendation website showcasing destinations with search functionality and visually engaging content.

    HTML 1

  5. synthetic-data-GANerator synthetic-data-GANerator Public

    Generative Adversarial Networks (GANs) to create synthetic images of malignant skin lesions. The implementation is inspired by MelanoGAN paper.

    Jupyter Notebook 1

  6. yolov9-object-detection-guide yolov9-object-detection-guide Public

    Fine-tune YOLOv9 for custom object detection with this step-by-step guide, including dataset preparation, training, validation, and inference tools.

    Jupyter Notebook 2