<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Dev on Antony Mapfumo</title><link>https://mapfumo.github.io/tags/dev/</link><description>Recent content in Dev on Antony Mapfumo</description><generator>Hugo -- gohugo.io</generator><language>en-us</language><lastBuildDate>Thu, 27 Apr 2023 12:02:35 +1000</lastBuildDate><atom:link href="https://mapfumo.github.io/tags/dev/index.xml" rel="self" type="application/rss+xml"/><item><title>Machine Learning web application using Python, Scikit-Learn, Flask</title><link>https://mapfumo.github.io/posts/machine-learning-flask/</link><pubDate>Thu, 27 Apr 2023 12:02:35 +1000</pubDate><guid>https://mapfumo.github.io/posts/machine-learning-flask/</guid><description>&lt;p>The scikit-learn Iris data-set consists of 3 (Setosa, Versicolour, and Virginica) species (50 samples per species, for a total of 150 samples) of the iris flower. Each sample has four measurements: sepal length, sepal width, petal length, petal width. Given these measurements a machine learning model can predict the iris specie with a high degree of accuracy. Here I demonstrate a machine learning web application using &lt;em>Python&lt;/em>, &lt;em>Scikit-Learn&lt;/em> machine learning library and &lt;em>Flask&lt;/em> web framework. The application is then deployed on an Amazon EC2 instance. The source is on &lt;strong>&lt;a href="https://github.com/mapfumo/iris-flask">GitHub&lt;/a>&lt;/strong>.&lt;/p></description></item><item><title>Programming with Google Go Specialization - A Brief Course Review</title><link>https://mapfumo.github.io/posts/go_specialisation/</link><pubDate>Sat, 22 Apr 2023 17:33:35 +1000</pubDate><guid>https://mapfumo.github.io/posts/go_specialisation/</guid><description>&lt;p>Go or &lt;a href="golang.org">GoLang&lt;/a> is an open source statically typed language that was created at Google by Rob Pike, Robert Griesemer, and Ken Thompson. It first appeared in Nov 2009 and has been rapidly gaining in popularity. Some of the language&amp;rsquo;s highlights include clean and highly accessible syntax, garbage collection, amazing native concurrency, fast compilation speed, excellent tooling, builtin documentation, good cross-platform support, ORM (Object-relational mapping ) library called GORM and excellent support for micro-services.&lt;/p></description></item></channel></rss>