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joe-naz01/README.md

Hi there 👋

🎓 Data Science and Machine Learning Portfolio

Welcome to my collection of applied Data Science and Machine Learning projects built using Python, scikit-learn, PyTorch, and transformer-based models. Each project demonstrates end-to-end workflows — from data preprocessing and feature engineering to model development, tuning, and interpretation.

DATA SCIENCE AND MACHINE LEARNING

  1. Supervised learning with scikit learn

  2. Unsupervised learning in Python

  3. Linear Classifiers in Python

  4. Machine Learning for Time-Series Data in Python

LARGE LANGUAGE MODELS

  1. Basics of LLMs in Python

  2. Deep Learning for Text with Pytorch

  3. Llama Basics

Popular repositories Loading

  1. DRO-Matic DRO-Matic Public

    C++

  2. Plant_AI Plant_AI Public

    Forked from soumyajit4419/Plant_AI

    Performing Leaf Image classification for Recognition of Plant Diseases using various types of CNN Architecture, For detection of Diseased Leaf and thus helping the increase in crop yield.

    Jupyter Notebook

  3. Image-Classification Image-Classification Public

    Forked from CheshtaK/Image-Classification

    Image Classification using SVM

    Jupyter Notebook

  4. Plant-Leaf-Disease-Detection-using-SVM Plant-Leaf-Disease-Detection-using-SVM Public

    Forked from manojkumar101/Plant-Leaf-Disease-Detection-using-SVM

    Single model which will be capable for detection of disease in various types of farming practices like floriculture, arboriculture, agriculture, cultivation, horticulture, etc.

    Jupyter Notebook

  5. html-portfolio html-portfolio Public

    HTML

  6. image-classification-28x28 image-classification-28x28 Public

    Develop and evaluate machine learning classifiers to categorize 28x28 grayscale images into predefined classes. Multiple algorithms are implemented and compared to identify the most accurate and co…

    Jupyter Notebook