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This is a complete solution of machine learning data mining competition Kaggle Telstra network disruption competition using xgboost ensemble
Learn about powerful R packages like amelia, missForest, hmisc, mi and mice used for imputing missing values in R for predictive modeling in data science.
Explore XGBoost parameters and hyperparameter tuning like learning rate, depth of trees, regularization, etc. to improve model accuracy.
Learn R Programming For Data Science, data manipulation, machine learning, with our guide covering everything from installation to predictive modeling.
A perfect guideline for doing optimal segmentation for model development. In this article learn about building predictive models using segmentation.
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.
Master data science & get hired at Google & Amazon. With books for data science, understand the predictive models statistically.
This is a complete learning path for newbies and beginners to learn R basics, machine learning, data mining with best free online resources
Solution to Big Mart sales problem - includes hypothesis, data exploration, feature engineering & regression, decision tree / random forest model
I learnt a lot about time series analysis by participating in AV Mini DataHack. I share my learnings from the competition.
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