Linear Regression is one of the most useful statistical/machine learning techniques. And we have multiple ways to perform Linear Regression analysis in Python including scikit-learn’s linear regression functions and Python’s statmodels package. statsmodels is a Python module for all things related to statistical analysis and it provides classes and functions for the estimation of many […]
Machine Learning
How To Compute Z-scores in Python
Computing standardized values of one or more columns is an important step for many machine learning analysis. For example, if we are using dimentionality reduction techniques like Principal Component Analysis (PCA), we will typically standardize all the variables. To standardize a variable we subtract each value of the variable by mean of the variable and […]
SVD: One Matrix Decomposition to Rule Them All
One of the nice things about twitter, when you follow awesome people, is that you will come across tweets that will just blow your mind. Last week is just one such week with some fantastic and funniest tweetorials. One of the tweetorials was from Prof. Daniela Witten for @WomenInStat. And it starts like this and […]
Principal Component Analysis with Penguins Data in Python
Who does not love PCA with Penguins in Python. Sorry, could not resist saying this :). If you are tired of seeing Iris data for introducing all things Machine Learning, Data Science algorithms and Data Visualization examples, you are in for much needed treat in the form of Penguins. Thanks to Alison Horst, who has […]
PCA with tidymodels in R
tidymodels, is one of the new suite of packages for doing machine learning analysis in R with tidy principles from RStudio. Tidymodels, the metapackage, has a core set of packages for statistical/machine learning models like infer, parsnip, recipes, rsample, and dials in addition to the core tidyverse packages dplyr, ggplot2, purr, and broom. In addition […]