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You are here: Home / Archives for Machine Learning

Machine Learning

Singular Value Decomposition (SVD) in Python

May 25, 2019 by cmdlinetips

SVD Scree Plot

Matrix decomposition by Singular Value Decomposition (SVD) is one of the widely used methods for dimensionality reduction. For example, Principal Component Analysis often uses SVD under the hood to compute principal components. In this post, we will work through an example of doing SVD in Python. We will use gapminder data in wide form to […]

Filed Under: Dimensionality Reduction, Singular Value Decomposition, SVD in Python, SVD with NumPy Tagged With: Dimensionality Reduction, Singular Value Decomposition in Python, SVD in NumPy, SVD in Python

Implementing K-means clustering in Python from Scratch

May 5, 2019 by cmdlinetips

K-means Cluster Assignment: Third Iteration

K-means clustering is one of the commonly used unsupervised techniques in Machine learning. K-means clustering clusters or partitions data in to K distinct clusters. In a typical setting, we provide input data and the number of clusters K, the k-means clustering algorithm would assign each data point to a distinct cluster. In this post, we […]

Filed Under: K-means clustering, K-means clustering example Python, K-means clustering in Python, Machine Learning Tagged With: K-means clustering, K-means clustering in Python, Machine Learning, Machine Learninhg

PCA example using prcomp in R

April 28, 2019 by cmdlinetips

PCA plot

In this tutorial, we will learn how to perform PCA in R using prcomp() function in R. Principal Component Analysis, aka, PCA is one of the commonly used approaches to do unsupervised learning/ dimensionality reduction. It is a fantastic tool to have in your data science/Machine Learning arsenal. You will be surprised how often the […]

Filed Under: PCA example in R, PCA prcomp example, PCA with prcomp, PCA with R, Principal Component Analysis, R, R Tips Tagged With: PCA example in R, PCA prcomp example, PCA tutorial in R, PCA with R, prcomp in R, Principal Component Analysis

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