Dataflow Programming for Machine Learning in R
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Updated
May 28, 2024 - R
Dataflow Programming for Machine Learning in R
Ground water age predictor
Sentiment Classification with Bagging and SVM
This project employs ensemble learning methods to forecast cybercrime rates, utilizing datasets with population, internet subscriptions, and crime incidents. By analyzing trends and employing metrics like R2 Score and Mean Squared Error, it aims to enhance prediction accuracy and provide insights for effective prevention strategies.
"This repository contains implementations of Boosting method, aimed at improving predictive performance by combining multiple models. by using titanic database."
This notebook explores fraud detection using various machine learning techniques.
Analyze the data and come up with a predictive model to determine if a customer will leave the credit card services or not and the reason behind it
Regression, Classification, Clustering, Dimension-reduction, Anomaly detection
A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.
Scikit learn oriented utils
Introduction to tree models with Python
The folliwing ML project involves EDA analysis of Election Dataset, Data preparation for modelling, and prediction using ML models. Also Text Analysis on the inaugral corpora from nltk to analyse the most frequently used words in Presidents' Speeches.
Bank Credit Card Customer churn prediction
The purpose of this project is to try to predict the occurrence of injuries based on player's in-game statistics.
These are some exercises and implementations to use multiple nodes of GPUs
Code to reproduce figures of Debeire, K., Runge, J., Gerhardus, A., Eyring, V. (2024). Bootstrap aggregation and confidence measures to improve time series causal discovery
These training sessions in machine learning, conducted by Yandex, are dedicated to classical machine learning. This offers an opportunity to reinforce theoretical knowledge through practice on training tasks.
A web-based and machine-learning fostered prototype tool to find your best financial investment portfolio
This is a R repository of studies that I made on some data sets. There are linear models, predicition models (boosting - bagging - RandomFlorest), clustering and dendograms.
Personal projects on AI and ML
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