GitHub topics: model-evaluation-and-selection
mkhekare/heart_ml
Predict the 10-year risk of coronary heart disease (CHD) using patient data from the Framingham Heart Study. The dataset contains over 4,240 records with 15 attributes, allowing for exploration, feature engineering, and the development of classification models
Language: Jupyter Notebook - Size: 362 KB - Last synced at: 20 days ago - Pushed at: 20 days ago - Stars: 0 - Forks: 0
vinothvk99/Bank-Marketing-Campaign-Prediction
Predicting the success of bank marketing campaigns using machine learning models (Random Forest, XGBoost) on customer and economic data. The project includes data preprocessing, model training, and evaluation with accuracy and ROC-AUC scores.
Language: Jupyter Notebook - Size: 905 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 0 - Forks: 0
JBris/clearml-testing
Testing out ClearML.
Language: Python - Size: 269 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
semyonsw/Diabetes_Dataset
Here I analysed data and made pipeline out of it making model making/training/testing/selecting and hyperparameters selecting more user friendly and visualised, like an application. I have worked for this project ~2 weeks.
Language: Jupyter Notebook - Size: 4.47 MB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 1 - Forks: 0
mpolinowski/yolo-i-know-flowers
YOLOv8 image classifier model comparison
Language: Jupyter Notebook - Size: 4.99 MB - Last synced at: 28 days ago - Pushed at: over 1 year ago - Stars: 5 - Forks: 1
serdaraydem1r/10DayAIChallenge101
In the 10-day camp, we experienced the basics of machine learning by coding
Language: Python - Size: 983 KB - Last synced at: 20 days ago - Pushed at: 8 months ago - Stars: 0 - Forks: 0
FarhanaTeli/Factors-Influencing-US-Home-Prices
Using publicly available data for the national factors that impact supply and demand of homes in US, build a data science model to study the effect of these variables on home prices.
Language: Jupyter Notebook - Size: 4.08 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
Arnyroid/fluffy-advertisement
This repository explores machine learning models applied to predict online shoppers' purchase intentions based on a comprehensive dataset, showcasing various classification algorithms and their performance in the e-commerce domain.
Language: Jupyter Notebook - Size: 383 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
ManunEbo/Home-Shopping-ML
This is an end to end machine learning project using my personal shopping data collected over the past three years.
Language: Jupyter Notebook - Size: 138 MB - Last synced at: about 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
mpolinowski/tf-i-know-flowers
Tensorflow image classifier Keras Applications model comparison
Language: Jupyter Notebook - Size: 7.61 MB - Last synced at: about 1 month ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 1
awesomecosmos/Insurance-Predictions
Repository to store materials for our group project on predicting health insurance charges.
Language: Jupyter Notebook - Size: 3.5 MB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 0
virchan/predictive_modeling_workflow
This project explores the predictive modeling workflow using the Kaggle competition "Titanic - Machine Learning from Disaster." It emphasizes key stages like data analysis and model evaluation, aiming to identify the optimal model. Through a real-world approach, we enhance our understanding of the workflow and emphasize rigorous model evaluation.
Language: Jupyter Notebook - Size: 2.48 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
braimahm/Machine-Learning-Projects
These projects illustrate key machine learning concepts, model development, regression, predictions, model assessment, iterations, and parametrization in the context of operational forecasting
Language: Jupyter Notebook - Size: 15.5 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
lihuicham/default-credit-card-clients-prediction
A machine learning foundation project to predict defaulting credit card clients. Topics covered are EDA, feature engineering and selection, model evaluation.
Language: Jupyter Notebook - Size: 14.4 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0
sangita9853/Task-2-Data-Science-and-Business-Analytics
Graduate Rotational Internship Program -TSF-The Spark Foundation(Data Science and Business Analysis Internship) #GRIPJULY21-Task#2:Prediction Using Unsupervised Machine Learning-In this task, we have to predict the optimum number of clusters from the iris dataset & represent it visually.
Language: Jupyter Notebook - Size: 155 KB - Last synced at: almost 2 years ago - Pushed at: almost 4 years ago - Stars: 0 - Forks: 0
sangita9853/Task-2-LGM-Prediction-Using-Decision-Tree-Algorithm
Create the Decision Tree classifier and visualize it graphically. The purpose is if we feed any new data to this classifier, it would be able to predict the right class accordingly.
Language: Jupyter Notebook - Size: 165 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 2 - Forks: 0