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Learn about the challenges of imbalanced classification in R and how it can affect the accuracy of machine learning algorithms. Read Now!
This tutorial illustrates use of recommendation engines in the banking industry with practicals done in R. It also explains types of recommendation engines.
Learn how Principal Component Analysis (PCA) can help you overcome challenges in data science projects with large, correlated datasets. Read Now!
This article reveals the winning solutions of date your data competition. Winners used R, python and boosting algorithms to get winning scores
This article explains artificial neural networks and fundamentals of deep learning. Learn about forward and backward propagation.
This is a solution of mini hack excel which involves solving a business problem using advanced excel, logical and structured thinking to solve
This is a tutorial on creating maps, scatter plots, bar plots, box plots, heat maps, area chart, correlogram using ggplot package in R
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.
A perfect guideline for doing optimal segmentation for model development. In this article learn about building predictive models using segmentation.
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