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A framework to quickly build a predictive model using python in under 10 minutes & create a benchmark solution for data science competitions.
Learn how to build a predictive model. This article teaches ways to build predictive models by saving time during data modeling, data treatment analysis.
Python and R cheat sheets for machine learning algorithms. It contains codes on data science topics, decision trees, random forest, gradient boost, k means.
Gradient boosting is used for improving prediction accuracy. This tutorial explains the concept of gradient boosting algorithm in r with examples.
This article explains the use of forward selection techniques in ensemble modeling using R programming with a careful attempt to avoid overfitting
This article explains the method to find optimal weight in ensemble model using a traditional approach and neural network implementation.
List of best machine learning certifications and best data science bootcamps in the USA. This article explains the best free resources on machine learning.
Knn algorithm is a supervised machine learning algorithm. In this article learn the concept of kNN in R and knn algorithm examples with case study.
Regression techniques are the popular statistical techniques used for predictive modeling. Learn common types of regression techniques.
A tutorial to learn about the basics of ensemble learning and various ensemble learning techniques to improvise stability and predictive power of the model.
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