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🌟 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning techniques and pre-trained models to accurately identify and categorize images based on their respective classes.
Our goal is to train a classifier that can predict the CEFR level of any given sentence. In this notebook we will use 🤗Hugging Face and its transformers library as the training framework, with Pytorch as the deep learning backend.
This project aims to predict rainfall using machine learning techniques. It utilizes historical weather data and applies machine learning algorithms to predict rainfall for future time periods. The prediction model is built using Python programming language and popular machine learning libraries.
A Bachelor's Thesis project analyzing and comparing classifiers for breast cancer detection using fine needle aspiration biopsies. Includes Jupyter Notebooks for model training and evaluation, and a LaTeX document detailing the methodology and results. Features SHAP for explainable AI analysis.
This repository contains two implementations of a K-Nearest Neighbors (KNN) classifier for predicting online shopping behavior. The classifiers are implemented in Python and use different approaches for finding the nearest neighbors: Naive Implementation, KDTree Implementation
The File Classifier is a Python script that monitors a specified directory (typically the Downloads folder) and automatically organizes files into different folders based on their file types.
Projects developed for the Machine Learning Introduction course, where I built a classifier and a regressor model using the Scikit-Learn library in Python.