PCA is a linear dimensionality reduction technique. Many non-linear dimensionality reduction techniques exist, but linear methods are more mature, if more limited.

Homer, a text analyser in Python, can help make your text more clear, simple and useful for your readers.

High-performance Linux log viewer and analyzer.

SolarWinds® Loggly® makes Linux log monitoring and analysis simple with a powerful platform that can correlate all your logs for a unified view of your environment. It offers cloud-based log aggregation with an agentless approach for collecting logs.

You can use simple scripts to configure your Linux files and directories to send logs to Loggly. Alternatively, you can also use the syslog daemon to send Linux system logs to Loggly for file and application log monitoring. A major advantage of Loggly is that it has a highly intuitive interface with simpler workflows. Unlike other tools, you don’t have to spend countless hours in the initial setup. Loggly automatically archives your older logs on AWS S3 buckets for compliance.

Say you have an external hard drive with layers upon layers of cryptically named folders and intricate mazes of directories (like here, or here). How can you make sense of this mess? Python offers various tools in the Python standard library to deal with your file system and the folderstats module can be of additional help to gain insights into your file system.

In this article, you will learn the various ways to traverse and explore the file system with Python. In the next section, you will see how to extract statistics from files and directories. In the last section, you will see a practical way to analyze folder structures with folderstats and Pandas with some use cases and visualizations along the way.

Tracking happiness is very simple. This section explains the method used for tracking happiness