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This is a complete solution of machine learning data mining competition Kaggle Telstra network disruption competition using xgboost ensemble
Explore XGBoost parameters and hyperparameter tuning like learning rate, depth of trees, regularization, etc. to improve model accuracy.
Take your GBM models to the next level with hyperparameter tuning. Find out how to optimize the bias-variance trade-off in gradient boosting algorithms.
Solution to Big Mart sales problem - includes hypothesis, data exploration, feature engineering & regression, decision tree / random forest model
In this article text mining capability of Graphlab is exploited to solve one of the Kaggle problems, taking into consideration the sentiment of each phrase.
Complete guide to Time series forecasting in python and R. Learn Time series forecasting by checking stationarity, dickey-fuller test and ARIMA models.
Learn how multinomial and ordinal logistic regression in R are used to deal with multi-level independent variables. Read Now!
Explore Ridge and Lasso Regression, their mathematical principles & practical applications in Python to enhance regression skills. Read Now!
XGBoost is an efficient gradient boosting framework. Say goodbye to lengthy feature engineering as XGBoost in R takes new heights!
This Python tutorial focuses on the basic concepts of Python for data analysis. Learn Python to expand your knowledge and skill set for data science.
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