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edaaydinea / OP1-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease

Star 10

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD).

data-science machine-learning deep-neural-networks tensorflow neural-networks logistic-regression keras-neural-networks chi-square-test random-forest-classifier alzheimer-disease-prediction xgboost-classifier anova-test lightgbm-classifier catboost-classifier multi-layer-perceptron-classifier
  • Updated Nov 6, 2022
  • Jupyter Notebook

edaaydinea / OP2-Prediction-of-the-Different-Progressive-Levels-of-Alzheimer-s-Disease-with-MRI-data

Star 9

This is an optional model development project on a real dataset related to predicting the different progressive levels of Alzheimer’s disease (AD) with MRI data.

data-science machine-learning deep-learning tensorflow neural-networks logistic-regression keras-neural-networks chi-square-test random-forest-classifier xgboost-classifier lightgbm-classifier smote-oversampler anova-analysis catboost-classifier multi-layer-perceptron-classifier
  • Updated Nov 6, 2022
  • Jupyter Notebook

sachin17git / Malware-detection-ML

Star 3

Android malware detection using machine learning.

python machine-learning random-forest machine-learning-algorithms feature-selection logistic-regression bayesian-inference support-vector-machines bayesian-optimization multicollinearity k-nearest-neighbours malware-detection voting-classifier shapley-values xgboost-classifier shap-values shapley-additive-explanations catboost-classifier stacking-classifier
  • Updated Nov 23, 2022
  • Jupyter Notebook

dharmendradiwaker / Forecasting-House-Prices-Using-Machine-Learning

Star 1

This project focuses on predicting house prices using machine learning techniques. The dataset consists of over 1,000,000+ rows and 12 columns containing information about various house attributes. The goal is to build predictive models to estimate house prices based on these attributes.

machine-learning random-forest gradient-descent decision-trees scikitlearn-machine-learning catboost-classifier
  • Updated Nov 18, 2024
  • Jupyter Notebook

DanniRodrJ / milling-machine_failure-prediction

Star 1

Machine Learning aplicado al mantenimiento predictivo. Se realizaron 2 modelos: 1 por medio de clasificación binaria que predice si una máquina fresadora estará en riesgo de fallar o no, y el 2 modelo a través de clasificación multiclase que predecirá el modo de falla

python sklearn logistic-regression decision-tree-classifier binary-classification svm-classifier multilabel-classification gridsearchcv randomsearch optuna smotetomek pickle-file near-miss catboost-classifier
  • Updated Nov 8, 2023

kunalshelke90 / Predict-Bank-Credit-Risk-using-South-German-Credit-Data

Star 1

This is an end-to-end ML project, which aims at developing a classification model for the problem of classifying a given customer profile into either of the risk category (safe or not safe). The final classifier used for this project is CatBoost classifier. Deployed in AWS.

python dockerfile flask aws finance data-science data machine-learning cassandra numpy logging pandas classification financial-analysis dataanalysis credit-risk mlflow github-actions catboost-classifier
  • Updated Sep 4, 2024
  • Jupyter Notebook

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