binaryclassification | Topic | Ecosyste.ms: Repos

Topic: "binaryclassification"

PacktWorkshops/The-Data-Science-Workshop

A New, Interactive Approach to Learning Data Science

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dr-mushtaq/Deep-Learning

This repository is a related to all about Deep Learning - an A-Z guide to the world of Data Science. This supplement contains the implementation of algorithms, statistical methods and techniques (in Python)

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AdityaTheDev/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

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sagnik1511/Loan-Web

ML-powered Loan-Marketer Customer Filtering Engine

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Gokul-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

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Koldim2001/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

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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.

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ThecoderPinar/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.

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PhenomSG/CV-based-Waste-Identifier

A computer vision-based waste identifier utilizes advanced image processing techniques and machine learning

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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.

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Sanky18/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.

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ssharanyab/Rice-Classification

Classification of two varients of rice - Osmancik, and Cammeo using machine learning

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nataberishvili/nataberishvili.github.io

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Ansuman21/Evaluating_and_Optimizing_Model_Performance_for_Business_Decision-Making

Data Science Project (Understanding Classification Model Performance Metrics M5)

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CLoaKY233/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.

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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.

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mattsankner/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

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AfnanHashmi/Crack-Detector

The model is trained on the dataset from kaggle. used CNNs for training model. Has a accuracy of 97%.

Language: Python - Size: 7.81 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0

lmihaig/EuroparlClimateVotes

This project was built within 24h by the team Augusteam for the DevHacks 2022 Climate Change hackathon sponsored by Systematic and it won the third place worth 500€

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zurain2001/Data-Science-Coursework

Individual projects done for the Data Science class

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Pratik-Prakash-Sannakki/AutoML_Multi_binaryClassifications_regression

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GaneshJainarain/BinaryClass_PulsarData_Kaggle

The dataset for this competition (both train and test) was generated from a deep learning model trained on the Pulsar Classification.

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SheezaShabbir/FaceVerification-using-CNN-Custom-model

Implementing a model that can verify if two images belongs to same personality or not. Answer the question "Is this the claimed person?" It is a 1:1 matching problem i.e. given a face your task is to compare the candidate face to another and verify whether it is a match or not. My custom CNN model has achieved marvelous performance on the dataset.

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0xN1nja/Spam-Ham-Classification-Using-TensorFlow-NLP

NLP Model for Spam/Ham Mail Classification

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ZahraDehghani99/Parkinson-Disease-Classification

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nischaybikramthapa/predicting-hospital-los

Can we predict how long a patient will be in a hospital with a fair comparison on gender, race and health service areas?

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saurabh48782/Customer_Attrition_Prediction

The goal of the project is to build a predictive model using machine learning concepts to predict customer attrition for a telecom service company.

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sharmila-polamuri/sentiment_analysis

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singhvks/Loan-approval

DECISION TREE CLASSIFIER - HYPER PARAMETER TUNING - Binary Classification

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abhinavthapper31/Sentiment-Analysis-on-Product-Reviews

Text Classification Problem : Wrote a module to classify Amazon-Product Reviews as favourable/unfavourable. Achieved accuracy of 78% and an F1 score of .81 using Logistic Regression on a test-train split of 20%, where total records were around 50000.

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divyanshu132/Bank-Customer-Churn-Prediction

Language: Python - Size: 297 KB - Last synced at: 10 months ago - Pushed at: over 6 years ago - Stars: 1 - Forks: 2

itsfk/Binary-Classification-Using-Keras-On-HR-Data

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AqueeqAzam/Football-Match-Winner-Prediction-using-Artificial-Neural-Networks

A neural network model that predicts whether Team A will win a football match using match statistics like average goals, possession, yellow cards, and game conditions. The project uses a fully connected deep learning model (FCNN) trained on real match data to forecast win probabilities.

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Code-str8/customer-frauds-detection

fraud detection challenge for STEG (Tunisian Company of Electricity and Gas) focused on identifying fraudulent meter manipulation through billing history data

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NiranjanRao07/data-245-assignments

This repository documents my journey through a curriculum focused on classical machine learning techniques, blending both theoretical foundations and hands-on implementation.

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MohammedSaqibMS/Building-your-Deep-Neural-Network

This repository guides you in building deep neural networks from scratch using Python and NumPy, covering key concepts like forward propagation and cost functions for binary classification.

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steveee27/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."

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SriNeogi/Deals-Prediction-Python

Binary Classification problem (Won = 1, Lost=0)

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Akashvarma26/Customer-Churn-Project

Customer churn classifier using ANN and deploying into streamlit.

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VigKu/Chronic_Kidney_Disease-

Determining if patients progress in their CKD stage in the future.

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saranya-ponnarasu/Predictive_Lead_Scoring_for_Edtech

Predicting lead conversion rates using a Logistic Regression model for an EdTech company.

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SahandNamvar/Binary-classification-Alzheimer-disease

EDA, pre-processing, train & test models, select best-performing model based on accuracy, precision, recall, and F1-score

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shubhampundhir/dlv3plus_binaryClf_VideoAnalytics

Binary classification using DeeplabV3plus on E-marg(custom) dataset that comprises of images and video analytics.

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maryamsoftdev/Brain-Tumor-Detection-Computer-Vision-Task

sys

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Bernardbyy/SpotifyMusicClassifier

Spotify Music Classifier with Machine Learning Using Spotify API

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muscak/Diabetes-Risk-Prediction

Prediction of diabetes based on the signs and symptoms using machine learning algorithms

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PulkitGigoo99/Particle_Physics_Event_Classification

A Machine Learning Project for Event Classification into Signal or Background Noise

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gianpaolof/basic_binary_class_tf_lite

binary classification problem with tensor flow lite. very basic

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AdilAhmedunar/Internship_Project_on_Machine_Learning_Pipelines

Predicting Startup Acquisition Statuses using Machine Learning Pipelines!

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MdTanvirHossainTusher/Titanic-Survival-Prediction

A classifier that can predict whether a passenger can survive the sinking of the Titanic

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MdTanvirHossainTusher/Credit-Card-Fraud-Detection

A model for binary classification of credit card data as fraudulent or legitimate

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vennisabarfi/logistic-regression-model

Models Breast Cancer data to make predictions

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christinacdl/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

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KallistaXue/Titanic-passenger-survival-prediction

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.

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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.

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SheezaShabbir/Cherry_Leaf_Health_Detector_app

The "Cherry Leaf Health Detector" is a comprehensive repository housing a sophisticated Streamlit web application designed to assess the health of cherry leaves by distinguishing between healthy leaves and those affected by powdery mildew.

Language: Python - Size: 3.91 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0

FarhanaTeli/Kyphosis_Disease_Prediction_with_NN_XGBoost

Kyphosis disease prediction using simple Neural Network (NN) model and XGBoost model with GridSearchCV

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hariprasath-v/Machinehack_analytics_olympiad_2023

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.

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Kridosz/Loan-Default-Prediction_Model

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.

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PhenomSG/Cat-Dog-Classifier

A Python TensorFlow model classifying cat and dog images using deep learning techniques for accurate and efficient image recognition.

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saptarshi11/DiaMLP---Diabetes-Classification-with-Multilayer-Perceptron

Diabetes Classification using Multilayer Perceptron (MLP) is a binary classification problem where the goal is to predict whether a patient has diabetes (positive class) or not (negative class) based on a set of biomedical features or risk factors.

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Abhishekkohli/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.

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VectorNd/Customer_Default_Prediction

Predict whether a customer will default in the future

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hariprasath-v/DOCEREE_machine-learning-hackathon_round_1

Create a model that can accurately predict whether a user belongs to the HCP(Healthcare Professional) category or not. Based on server logs.

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richasingh-92/Machine-Learning-Pipelines-with-Azure-ML-Studio

The aim of this project is to check if an adult has income exceeding 50k per year based on the census data.For the following project, I have used the Decision Tree (Booster) algorithm to create and train the model. The model is available as an azure model web service.

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