A computer vision-based waste identifier utilizes advanced image processing techniques and machine learning
-
Updated
Oct 13, 2023 - Jupyter Notebook
A computer vision-based waste identifier utilizes advanced image processing techniques and machine learning
Develop a technology for detecting mining sites using images from the optical satellite Sentinel-2. Specifically, it involves classifying images that contain mining sites and those that do not.
A model for binary classification of credit card data as fraudulent or legitimate
This is heart disease prediction project that contains different methods such as FNN with Multiclass Classification, Binary Classification, Cross-Validation etc.
Analysis of the credit history of a user and to predict if the user is a suitable candidate for a small ticket loan.
Duke University project: Data analysis in Excel (statistical analysis)
Histogram based classification and prediction of annual rainfall from Kerala dataset
Loan Default Prediction Model: A machine learning project that leverages historical lending data to create predictive models for assessing loan default risk, aiding financial institutions in making informed lending decisions.
Social media fake accounts and spam accounts have become a huge problem these days. Some had spammed me twice on Instagram. Here I have used various Machine learning techniques to spot the fake/spam accounts
Create a machine learning model to determine the likelihood of a customer defaulting on a loan based on credit history, payment behavior, and account details.
Kyphosis disease prediction using Fully Connected Neural Networks (FCNNs) model and XGBoost model with GridSearchCV
Machine Learning Analysis and Prediction of Titanic Passenger Survival: A comprehensive project employing data preprocessing, exploratory analysis, and predictive modeling to unveil insights and predict outcomes from the Titanic disaster dataset.
Predicting Startup Acquisition Statuses using Machine Learning Pipelines!
Binary Classification of mnist data using Stochastic Gradient Descent(SGD)
Heart Failure Prediction using Machine Learning Techniques
Prediction of diabetes based on the signs and symptoms using machine learning algorithms
Insurance companies take risks over customers. Risk management is a very important aspect of the insurance industry. Insurers consider every quantifiable factor to develop profiles of high and low insurance risks. Insurers collect vast amounts of information about policyholders and analyze the data.
The task here is to predict whether a bank currency note is authentic or not based on four attributes i.e. variance of the image wavelet transformed image, skewness, entropy, and curtosis of the image.
Classifier using supervised machine learning algorithm which can accurately predict whether or not the patients in the dataset have diabetes.
Add a description, image, and links to the binaryclassification topic page so that developers can more easily learn about it.
To associate your repository with the binaryclassification topic, visit your repo's landing page and select "manage topics."