Popular GitHub Repositories for Ham

[MICCAI 2023] DermoSegDiff: A Boundary-aware Segmentation Diffusion Model for Skin Lesion Delineation

A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link

This is a Text Analysis App which can be used to find a detailed analysis of a particular text. This includes 5 main types of Analysis - Spam/Ham Detection, Sentiment Analysis, Stress Detection, Hate & Offensive Content Detection, Sarcasm Detection

A Natural Language Processing with SMS Data to predict whether the SMS is Spam/Ham with various ML Algorithms like multinomial-naive-bayes,logistic regression,svm,decision trees to compare accuracy and using various data cleaning and processing techniques like PorterStemmer,CountVectorizer,TFIDF Vetorizer,WordnetLemmatizer. It is implemented using LSTM and Word Embeddings to gain accuracy of 97.84%.

? E-mail Spam Filter using Naive Bayes ? Classifies emails as spam or non-spam (ham) using content analysis ? Demonstrates machine learning pipeline: preprocessing → training → evaluation ? Tools: Pandas, Scikit-learn, Jupyter Notebook

The CW (Morse) Generator is a versatile and powerful application for Morse communication enthusiasts and anyone interested in learning or practicing this classic language of communication. This software allows you to convert text to Morse code and vice versa, providing a complete suite of tools to create, interpret, and reproduce ...

Notebooks of pre trained models using the HAM10000 dataset

This project focuses on classifying spam/ham emails, using machine learning algorithms like LGR, NB, RF, DT etc.. and based on the accuracy score and precision score I chose logistic regression for the classification. And I have used streamlit for frontend.

This is a project that I worked on with my colleagues in the 6th Semester of my B.tech. In this project, we present a fully automatic method for skin lesion segmentation by leveraging UNet and FCN that is trained end to-end. For Skin lesion disease classification, we use a customized convolutional neural net. Designing a novel loss function based on Jaccard distance to eliminate the need of sample re-weighting, a typical procedure when using cross entropy as the loss function for image segmentation due to the strong imbalance between the number of foreground and background pixels.  Evaluated the effectiveness, efficiency, as well as generalization capability of the proposed framework on publicly available PH2 database and HAM10000 dataset.

Deep Learning based Skin Cancer Detection using multiple CNN architectures (VGG, ResNet, DenseNet, EfficientNet, Inception) with image preprocessing using ESRGAN and performance comparison for clinical AI research.

? A FastAPI-powered project that uses a trained ML model to classify incoming emails as spam ? or ham ? in real-time. Supports CSV batch processing ?, multi-query input ?, and detailed logging with usage stats ?.

End-to-end network security project using phishing data, featuring ETL pipelines, a spam/ham classification model, experiment tracking with MLflow, Docker-based containerization, and deployment on AWS Cloud.

The goal of this project is to build a machine learning model that automatically classifies emails as spam (unwanted) or ham (legitimate). The model will be trained on a labeled dataset and use features extracted from the email content to predict whether an email is spam or not.

A spam classifier is a software or machine learning model that categorizes incoming messages or content as either "spam" (unwanted or irrelevant) or "ham" (legitimate or relevant), using automated techniques.

A Python-based machine learning model for spam detection leveraging TF-IDF vectorization and multiple classifiers, including Naive Bayes, Logistic Regression, and Random Forest. This project demonstrates preprocessing techniques, model training, and performance evaluation for classifying SMS messages as spam or ham.

AI agent framework for amateur radio

PAARAbot is an application that tracks a list of call signs for POTA or SOTA activations and posts a message on Discord with the activation details. Originally developed by KN6YUH for the Palo Alto Amateur Radio Association Discord server.