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Learn how to build a predictive model. This article teaches ways to build predictive models by saving time during data modeling, data treatment analysis.
Gradient boosting is used for improving prediction accuracy. This tutorial explains the concept of gradient boosting algorithm in r with examples.
Learn why tuning machine learning algorithms is essential, explore Random Forests, their parameters and case studies for implementation.
This article introduces the science behind k-fold cross validation & its use in simple terms and explains its implementation in Python
Boosting is a powerful tool in machine learning. Learn the commonly used boosting algorithms Ada Boost, Gradient Boost, Gentle Boost, Brown boost.
Scikit-learn is a powerful Python library for machine learning & predictive modeling. This scikit learn tutorial gives an overview of scikit learn in python
Caret package in R provides the tools for building predictive models in R. In this tutorial learn the basics of the Caret package using a dataset in R.
Support vector machines are very effective. This article explains about the svm classification algorithm, its working and its uses.
Confused between the choices of classification model, i.e random forest or cart model. This article lays out a framework to make this choice.
This article brings out the differences in widely used CART and random forest model using simple case study and example.
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