Build a Web App called AI-Powered Heart Disease Risk Assessment App
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Updated
Jun 6, 2024 - HTML
Build a Web App called AI-Powered Heart Disease Risk Assessment App
A solid foundational understanding of XAI, primarily emphasizing how XAI methodologies can expose latent biases in datasets and reveal valuable insights.
A game theoretic approach to explain the output of any machine learning model.
A methodology designed to measure the contribution of the features to the predictive performance of any econometric or machine learning model.
Estudo transversal que analisou dados retrospectivos de gestantes e puérperas com diagnóstico de Síndrome Respiratória Aguda Grave (SRAG) entre janeiro de 2016 e novembro de 2021.
Accurate prediction of CRISPR-Cas9 off-target activity by learning to utilize internal protein 3D nanoenvironment descriptors
This repository includes a machine learning modeling study about estimating customers hotel cancellation and what are the reasons for these cancellations.
scripts used for neural decoding of single and multi unit auditory cortex data
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Performed model evaluation using evaluation metrics such as accuracy, precision, recall, F1-score etc. Then model interpretation using feature importance, SHAP and LIME. Finally , evaluated model robustness and stability through techniques like bootstrapping or Monte Carlo simulations.
A Bachelor's Thesis project analyzing and comparing classifiers for breast cancer detection using fine needle aspiration biopsies. Includes Jupyter Notebooks for model training and evaluation, and a LaTeX document detailing the methodology and results. Features SHAP for explainable AI analysis.
A web app developed for my Bachelor's Thesis to compare classifiers for detecting malignant tumors from fine needle aspiration biopsies. It includes classifier metrics, SHAP analysis for feature contributions, a classifier comparison tool, and a project overview slideshow.
Efficient R implementation of SHAP
This project uses machine learning to predict diabetes and provides explanations through SHAP and PCA, displayed in an intuitive user interface.
В данном репозитории хранятся выполненные мною проекты, в рамках обучения на курсе Яндекс. Практикума "Специалист по Data Science"
Weighted Shapley Values and Weighted Confidence Intervals for Multiple Machine Learning Models and Stacked Ensembles
ImputeVIS - eXascale Infolab, University of Fribourg, Switzerland
This repository contains the Python scripts that I have written and run to execute a series of analytic model developments using datasets taken from the book "The Elements of Statistical Elements" by Hastie, Tibshirani, Friedman
gradient-boosted regression and decision tree models on behavioural animal data
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