Increasingly, we have multiple high dimensional datasets from from the same samples. Canonical Correlation Analysis aka CCA is great for scenarios where you two high dimensional datasets from the same samples and it enables learning looking at the datasets simultaneously. A classic example is audio and video datasets from the same individuals. One can also […]
How To Code a Character Variable into Integer in Pandas
Often while working with a Pandas dataframe containing variables of different datatypes, one might want to convert a specific character/string/Categorical variable into a numerical variable. One of the uses of such conversion is that it enables us to quickly perform correlative analysis. In this post, we will see multiple examples of converting character variable into […]
Introduction to Canonical Correlation Analysis (CCA) in R
Canonical Correlation Analysis or CCA is a dimensionality reduction technique like Principal Component Analysis (PCA) or SVD. PCA/SVD aims to find the directions or projections that account for most of of the observed variance in a single high-dimensional data. In comparison, CCA deals with two high dimensional datasets and aims to find directions or projections […]
Book Review: Learn Coding Basics with Python for Kids
Recently I have been on the look out for buying a book or two for learning to code in Python, but for kids age 10 and above. Definitely there are a few options out there, but it was not easy to come up with a book to start with. Here is a bit of background. […]
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 […]