📻 Proof-of-concept project for detecting and classifying hyperbolas in ground penetrating radar (GPR) data.
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Updated
Aug 24, 2018 - Python
📻 Proof-of-concept project for detecting and classifying hyperbolas in ground penetrating radar (GPR) data.
A Machine Learning Model that classifies the data in the images as Sensitive or Non-sensitive.
Machine learning is widely used in bioinformatics and particularly in breast cancer diagnosis. In this project, certain classification methods such as K-nearest neighbors (K-NN) and Support Vector Machine (SVM) which is a supervised learning method to detect breast cancer are used.
A very simple Random Forest Classifier implementation in python.
A Keras deep learning image classifiers on Django server with REST API | Django 图片识别平台
Detecting Malware in PE files
An image recognition model which is capable of identifying the pattern on a dress image
Natural Language Processing of academic papers for dataset indexing
Deploy image classifier on a static website using javascript.
Using YOLOv8 to build a Object Classifier/Tracker for RBG/Thermal Cameras
With some projects to develop "TOOLs" for better Modeling
A Simple code to train a CNN to predict label of Covid and Non-Covid CT scan images and an ACGAN to generate them.
CM3P (Contrastive Metadata-Map Masked Pre-training) multi-modal representation learning framework for osu! beatmaps
Ozone Day AdaBoostClassifier and Random Forest Tree Classifier with Machine Learning
Data Science project. ML algorithms to detect voice disorders.
To build an AI-based classifier model to assign the tickets to right functional groups by analyzing the given description
IrisWise is a machine learning application for predicting Iris flower species. Built with Streamlit, this app provides a user-friendly interface to input flower measurements and receive predictions using various models, including K-Nearest Neighbors, (Random Forest, SVM, and Logistic Regression) **(Working On It...)**.
titania: a binary classifier that estimates the likelihood of hypothetically surving the titanic incident.
This repository contains a machine learning model that predicts SMS spam, with data cleaning, EDA, and preprocessing. The model has been deployed using Streamlit, and code and necessary files are included.
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