A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
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Updated
Jun 16, 2024 - Python
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
To design a predictive model using xgboost and voting ensembling techniques and extract insights from the data using pandas, seaborn and matplotlib
Analysing the content of an E-commerce database that contains list of purchases. Based on the analysis, I develop a model that allows to anticipate the purchases that will be made by a new customer, during the following year from its first purchase.
The official implementation of "The Shapley Value of Classifiers in Ensemble Games" (CIKM 2021).
[ECCV-20] Official PyTorch implementation of HoughNet, a voting-based object detector.
Fake News Detection System for detecting whether news is fake or not. The model is trained using "Liar, Liar Pants on Fire": A New Benchmark Dataset for Fake News Detection. Link for dataset: https://arxiv.org/abs/1705.00648.
Binary Classification for detecting intrusion network attacks. In order, to emphasize how a network packet with certain features may have the potentials to become a serious threat to the network.
In this project, the success results obtained from SVM, KNN and Decision Tree Classifier algorithms using the data we have created and the results obtained from the ensemble learning methods Random Forest Classifier, AdaBoost and Voting were compared.
Using Classification Techniques, Data reprocessing, Feature Engineering, Feature Extraction and Classification Algorithms from Machine Learning to Predict who can Survive the attack of Tsunami.
Contains code for a voting classifier that is part of an ensemble learning model for tweet classification (which includes an LSTM, a bayesian model and a proximity model) and a system for weighted voting
Classifying Audio to Emotion
This repository demonstrates the project dissertation topic at Kingston University (London)
Forecasting the likelihood of a customer defaulting their auto loan using classification models
Heart Disease Prediction using machine and deep learning techniques works on heart dataset
Tour of Machine Learning Algorithms for Binary/Multiclass Classification
A model build on RAVDESS dataset, for speech emotion recognition. 85.59% validation accuracy
A repository covering all my work on various topics and algorithms while learning Data Science, Machine Learning and Deep Learning.
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