Master Generative AI with 10+ Real-world Projects in 2025!
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.
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.
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