Machine Learning

Run in Google Colab View source on GitHub Download notebook In this post, we will read multiple csv files using Tensroflow Sequence. In an earlier post we had demonstrated the procedure for reading multiple csv files using a custom generator.

Run in Google Colab View source on GitHub Download notebook In many engineering applications data are usually stored in CSV (Comma Separated Values) files. In big data applications, it’s not uncommon to obtain thousands of csv files.

Run in Google Colab View source on GitHub Download notebook In this post, we will read multiple .csv files into Tensorflow using generators. But the method we will discuss is general enough to work for other file formats as well.

Run Python code in Google Colab Download Python code Download R code (R Markdown) In this post, we will reproduce the results of a popular paper on PCA. The paper is titled ‘Principal component analysis’ and is authored by Herve Abdi and Lynne J.

Run Python code in Google Colab Download Python code Download R code (R Markdown) Download MATLAB code This post is Part-II of a three part series post on PCA. Other parts of the series can be found at the links below.

In this post, we will discuss about Principal Component Analysis (PCA), one of the most popular dimensionality reduction techniques used in machine learning. Applications of PCA and its variants are ubiquitous.