Pinned Repositories
chama-data-transformation
JSON data parsing, transformation and manipulation; date and time handling; custom functions and row-wise processing; JSON payload transformation; data validation and error handling; CSV file generation
Data-Science
Data Science projects with R and Python
datasets
Just some datasets for my use
doordash-delivery-predictions
Prediction of delivery times for DoorDash deliveries. Performed feature engineering (creation, encoding), feature selection using (multi)collinearity analysis, Gini importance and PCA. Applied 6 ML models to perform regression analysis on delivery time prediction.
Fantasy-Premier-League
Creates a .csv file of all players in the English Player League with their respective team and total fantasy points
Humble-Beginnings
Basics of Data Science with Python. Special thanks to @llSourcell
karthikvadlamani
Config files for my GitHub profile.
reddit-dataisbeautiful
revolut-fraudsters-detection
Performed feature engineering, cross-validation (5 fold) on baseline and cost-sensitive (accounting for class imbalance) Decision trees and Logistic Regression models and compared performance. Used appropriate performance metrics i.e., AUC ROC, Average Precision and Balanced Accuracy. Outperformed baseline model.
rotten-tomatoes-movie-classification
Classification of movies as 'Fresh', 'Rotten', 'Certified-Fresh' using categorical predictors as well as review sentiment. Performed feature encoding and used Decision Tree, Random Forest Classifiers. Tackled class imbalance issues by assigning weights to classes. Used tokenization to generate word vectors for reviews to predict movie status.
karthikvadlamani's Repositories
karthikvadlamani/chama-data-transformation
JSON data parsing, transformation and manipulation; date and time handling; custom functions and row-wise processing; JSON payload transformation; data validation and error handling; CSV file generation
karthikvadlamani/Data-Science
Data Science projects with R and Python
karthikvadlamani/datasets
Just some datasets for my use
karthikvadlamani/doordash-delivery-predictions
Prediction of delivery times for DoorDash deliveries. Performed feature engineering (creation, encoding), feature selection using (multi)collinearity analysis, Gini importance and PCA. Applied 6 ML models to perform regression analysis on delivery time prediction.
karthikvadlamani/Fantasy-Premier-League
Creates a .csv file of all players in the English Player League with their respective team and total fantasy points
karthikvadlamani/Humble-Beginnings
Basics of Data Science with Python. Special thanks to @llSourcell
karthikvadlamani/karthikvadlamani
Config files for my GitHub profile.
karthikvadlamani/reddit-dataisbeautiful
karthikvadlamani/revolut-fraudsters-detection
Performed feature engineering, cross-validation (5 fold) on baseline and cost-sensitive (accounting for class imbalance) Decision trees and Logistic Regression models and compared performance. Used appropriate performance metrics i.e., AUC ROC, Average Precision and Balanced Accuracy. Outperformed baseline model.
karthikvadlamani/rotten-tomatoes-movie-classification
Classification of movies as 'Fresh', 'Rotten', 'Certified-Fresh' using categorical predictors as well as review sentiment. Performed feature encoding and used Decision Tree, Random Forest Classifiers. Tackled class imbalance issues by assigning weights to classes. Used tokenization to generate word vectors for reviews to predict movie status.
karthikvadlamani/tensorflow
Computation using data flow graphs for scalable machine learning