This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.
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Updated
Jun 8, 2024 - R
This project aims to predict heart failure outcomes by applying statistical learning algorithms. The goal is to improve the prediction accuracy through the SuperLearner algorithm.
Projeto de classificação desenvolvido em linguagem Python com objetivo de auxiliar uma instituição financeira a criar um programa de aconselhamento para clientes com altas probabilidades de inadimplência.
Projeto de classificação desenvolvido em linguagem Python com objetivo de auxiliar uma empresa de e-commerce a prever o risco de atraso na entrega de seus produtos.
Churn Analysis of Telecom company,Through meticulous data analysis and predictive modeling, we uncover patterns, trends, and potential churn triggers, empowering telecom companies to proactively mitigate customer attrition. Our mission is to equip industry stakeholders with actionable intelligence, enabling them to optimize retention strategies.
We leverage machine learning and data analysis to address real-world challenges in the copper industry. Our documentation encompasses data preprocessing, feature engineering, classification, regression, and model selection. Explore how we've enhanced predictive capabilities to optimize manufacturing solutions.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
End to End MLOps with Berka Bank Dataset and VertexAI
ML Projects
My portfolio website regarding data science projects. Some visualization and analysis projects reflect work for PITAPOLICY clients.
Highly Comparative Graph Analysis - Code for network phenotyping
Practices and Assignments from the Advanced Machine Learning Class
This repository houses a diverse collection of projects developed using Jupyter Notebooks, focusing on testing various machine learning pipelines, neural network models, and statistical machine learning approaches. Through exploration of different datasets, the projects delve into predictive modeling, classification tasks, and in-depth analyses.
Introduction to Data Science: Term Project (2021W) - Predictive Analysis
My Matlab Ph.D. thesis coding project: the enhanced version of Tree-like Divide to Simplify (T-DTS) ANN (AI/ML) structure-based tool used for classification tasks. The credits: the v.1.0 was developed by Dr. M. Rybnik under supervision of Prof. K. Madani
🍊 PAUSE (Positive and Annealed Unlabeled Sentence Embedding), accepted by EMNLP'2021 🌴
Algorithm to classify between AI and non AI arts
Python program to Predicting Stars Galaxies Quasars with ML Model
Fast Best-Subset Selection Library
Applied Data Science Project
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