Pinned Repositories
Applying-Evaluating-Clustering-algorithms
This is a small tutorial project that demonstrates application and evaluation methods of popular clustering algorithms namely, K-means, DBSCAN and Agglomerative.
Cancer-Detection-and-Model-interpretability-using-SHAP-and-LIME
This project addresess a medical problem of detecting cancer and understanding what causes cancer in body using machine learning.
cardiovascular_disease_prediction-using-PCA-and-Xgboost
Detection of cardiovascular disease using AWS Sagemaker PCA and Xgboost techniques
Classification-suite-and-Methods-for-Performance-Evaluation
Predictive problems requires three main challenges to overcome. First, choosing the right classification algorithm. Second, building a robust building and testing environment for algorithm to learn and thirdly, picking the appropriate performance metric for evaluation. Here it is explained how these challenges can be addressed.
Improved-Predictive-Outcome-using-PCA
This project demonstrates application of PCA for improving the classification results
Multiple-Linear-Regression-with-Regularization
A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net
Parameter-tuning-Regression-algorithms
Different linear and non linear regression models are demonstrated with illustration on parameter tuning using GridsearchCV in sklearn
posts
Material for posts
Predicting-Parkinson-Disease-using-Machine-learning
This project addresses problem of early detection of Parkinson disease using Machine learning techniques
Predicting-rainfall-in-Kerala-using-Machine-learning-models
This project demonstrates machine learning pipeline to predict rainfall in Kerala state of India
sakshibabbar2019's Repositories
sakshibabbar2019/cardiovascular_disease_prediction-using-PCA-and-Xgboost
Detection of cardiovascular disease using AWS Sagemaker PCA and Xgboost techniques
sakshibabbar2019/Classification-suite-and-Methods-for-Performance-Evaluation
Predictive problems requires three main challenges to overcome. First, choosing the right classification algorithm. Second, building a robust building and testing environment for algorithm to learn and thirdly, picking the appropriate performance metric for evaluation. Here it is explained how these challenges can be addressed.
sakshibabbar2019/Multiple-Linear-Regression-with-Regularization
A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net
sakshibabbar2019/Parameter-tuning-Regression-algorithms
Different linear and non linear regression models are demonstrated with illustration on parameter tuning using GridsearchCV in sklearn
sakshibabbar2019/Predicting-Parkinson-Disease-using-Machine-learning
This project addresses problem of early detection of Parkinson disease using Machine learning techniques
sakshibabbar2019/Applying-Evaluating-Clustering-algorithms
This is a small tutorial project that demonstrates application and evaluation methods of popular clustering algorithms namely, K-means, DBSCAN and Agglomerative.
sakshibabbar2019/Cancer-Detection-and-Model-interpretability-using-SHAP-and-LIME
This project addresess a medical problem of detecting cancer and understanding what causes cancer in body using machine learning.
sakshibabbar2019/Improved-Predictive-Outcome-using-PCA
This project demonstrates application of PCA for improving the classification results
sakshibabbar2019/posts
Material for posts
sakshibabbar2019/Predicting-rainfall-in-Kerala-using-Machine-learning-models
This project demonstrates machine learning pipeline to predict rainfall in Kerala state of India
sakshibabbar2019/sakshibabbar2019
sakshibabbar2019/Xgboost-for-Detecting-Credit-card-Frauds
This project is to identify fraudulent credit transactions using Xgboost
sakshibabbar2019/XGBoost-Sagemaker-for-Forecasting-Sales
The objective of this project is to forecast weekly retail store sales based on historical data using XGBoost Sagemaker