binaryclassification
There are 0 repository under binaryclassification topic.
PacktWorkshops / The-Data-Science-Workshop
A New, Interactive Approach to Learning Data Science
Language:Jupyter Notebook 241dr-mushtaq / Deep-Learning
This repository offers video-based tutorials on Deep Learning concepts along with practical implementations using Python, TensorFlow, and Keras. It is designed for students, educators, and self-learners who want to understand the theory and apply it through hands-on projects.
Language:Jupyter Notebook 30AdityaTheDev / NudityDetection-Using-Deeplearning
Nudity/pornography detection using deeplearning. This model is trained using pretrained VGG-16. To know more about this check the readme file below
Language:Jupyter Notebook 17- Loan-Web
sagnik1511 / Loan-Web
ML-powered Loan-Marketer Customer Filtering Engine
Language:Python 15 - Language:Jupyter Notebook 5
nikolliervin / profanity-detection
This nuget package is designed to help you easily identify and detect profanity or bad words within a given sentence or string. It works under a simple binary classifier that has been built and trained using ML.NET for accurate and efficient detection of inappropriate language.
Language:C# 5Gokul-001 / Detection-Of-Malarial-Infected-Cells-Using-CNN
Malaria is a serious global health problem that affects millions of people each year. One of the challenges in diagnosing malaria is identifying infected cells from microscopic images of blood smears. Convolutional Neural Networks (CNNs) are a type of deep learning algorithm that have been used for image classification tasks etc
Language:Jupyter Notebook 4Koldim2001 / Binary_classification_of_users
Бинарная классификация пользователей образовательной платформы Stepic на тех, кто скорее всего пройдет курс до конца и тех, кто скорее всего покинет платформу. Модель способна давать предсказания по анализу поведения юзеров на сайте за первые 3 дня
Language:Jupyter Notebook 4PhenomSG / CV-based-Waste-Identifier
A computer vision-based waste identifier utilizes advanced image processing techniques and machine learning
Language:Jupyter Notebook 4Sanky18 / L-T-EduTech-Hackathon-at-SHAASTRA-IITM
Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
Language:Jupyter Notebook 4- Covid19-Vaccine-ML-Pipeline
kingabzpro / Covid19-Vaccine-ML-Pipeline
Designing your first machine learning pipeline with few lines of codes using Orchest. You will learn to preprocess the data, train the machine learning model, and evaluate the results.
Language:Jupyter Notebook 3 AHMEDSANA / Binary-class-Brain-Tumor-classification
In this we trained a model to detect if there is a tumor in the brain image given to the model. Meaning a model for binary class with an accuracy of above 90 for same and cross validation.
Language:Jupyter Notebook 2mattsankner / micrograd
I build the Micrograd autogradient engine, which is a functioning neural network with forward pass, backward propagation, and stochastic gradient descent, all built from scratch. This is derived from the great @karpathy micrograd lecture. Each notebook is complete with Andrei's lecture code and speech, as well as my own code, anecdotes and addition
Language:Jupyter Notebook 2SahandNamvar / Binary-classification-Alzheimer-disease
EDA, pre-processing, train & test models, select best-performing model based on accuracy, precision, recall, and F1-score
Language:Jupyter Notebook 2samya-ak / MNIST-binary-classification
Binary Classification of mnist data using Stochastic Gradient Descent(SGD)
Language:Jupyter Notebook 2Concrete cracking is a major issue in Bridge Engineering. Detection of cracks facilitates the design, construction and maintenance of bridges effectively.
Language:Jupyter Notebook 2srijan-Git1247 / ML.Net-Application-CarPricePrediction
A Binary Classification application to predict if a car price is good deal or not based on a set of attributes using FastTree trainer based on the Multiple Additive Regression Trees (MART).
Language:C# 2ssharanyab / Rice-Classification
Classification of two varients of rice - Osmancik, and Cammeo using machine learning
Language:Jupyter Notebook 2ThecoderPinar / ML-Perceptron-Project
This project demonstrates the implementation of the Perceptron algorithm for binary classification tasks. It includes various advanced features such as data augmentation, feature engineering, and deep learning techniques to enhance model performance and robustness.
Language:Jupyter Notebook 2Abhishekkohli / Titanic-Disaster-Classification-ML
TitanicClassification.py file contains project based on binary classification. The dataset comprises of data related to passengers and binary value of whether they survived or not.
Language:Python 1AfnanHashmi / Crack-Detector
The model is trained on the dataset from kaggle. used CNNs for training model. Has a accuracy of 97%.
Language:Python 1Ansuman21 / Evaluating_and_Optimizing_Model_Performance_for_Business_Decision-Making
Data Science Project (Understanding Classification Model Performance Metrics M5)
Language:Jupyter Notebook 1catalinalopera / ObjectClassification-
This project demonstrates how to build and train a Convolutional Neural Network (CNN) using TensorFlow and Keras to classify images as pizza or not pizza. The model uses image augmentation techniques to improve generalization and prevent overfitting, and is suitable for beginner-level computer vision tasks.
Language:Jupyter Notebook 1christinacdl / Climate_Activism_Stance_and_Hate_Event_Detection_CASE_2024
Developed system for the "Climate Activism Stance and Hate Event Detection" Shared Task at CASE 2024
Language:Python 1CLoaKY233 / Binary-Classifier-CNN
A Convolutional Neural Network (CNN) implementation using PyTorch and TensorFlow/Keras to classify images of cats and dogs. This project includes training scripts, model architectures, and instructions for easy setup and usage.
Language:Python 1GaneshJainarain / BinaryClass_PulsarData_Kaggle
The dataset for this competition (both train and test) was generated from a deep learning model trained on the Pulsar Classification.
hariprasath-v / Solafune_Finding_Mining_Sites
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.
Language:HTML 1Hhhpraise / age-gender-race-prediction
A multi-task deep learning model that predicts age, gender, and race from facial images using TensorFlow/Keras
Language:Python 1MrigankJaiswal-hub / DiabetesPrediction
Prediction Of Daibetes on the basis of following factors : - pregnancies , glucose , diastolic , triceps , insulin , bmi , dpf , age , diabetes
Language:Jupyter Notebook 1pedrocast7 / ML_Mood_Classification_from_tweets_with_Sklearn
A repository with a binary classification problem to explore some models and basic concepts of Machine Learning.
Language:Jupyter Notebook 1PulkitGigoo99 / Particle_Physics_Event_Classification
A Machine Learning Project for Event Classification into Signal or Background Noise
Language:Jupyter Notebook 1raianurag7800-dev / Credit-Card-Approval-Prediction
This web app makes predictions about a credit card applicant's likelihood of approval.
Language:Jupyter Notebook 1shubh-iiit / dlv3plus_binaryClf_VideoAnalytics
Binary classification using DeeplabV3plus on E-marg(custom) dataset that comprises of images and video analytics.
Language:Python 1steveee27 / Bank-Loan-Granting-Prediction-using-Backpropagation-Neural-Network
This project aims to build a model that predicts whether a loan application will be granted based on customer features such as age, income, credit history, and more. Using the Backpropagation Neural Network (BPNN) architecture, the model is trained to classify loan approvals as either "approved" or "denied."
Language:Jupyter Notebook 1VectorNd / Customer_Default_Prediction
Predict whether a customer will default in the future
Language:Jupyter Notebook 1
