Introduction Machine learning is a type of artificial intelligence (AI) that lets computers “learn” from the data they receive. In recent years, machine learning has become increasingly popular and is used in everything from search engines to autonomous cars. This guide will help you understand what machine learning is, how […]
Month: April 2022
Introduction The cloud is changing the way we do business. It’s changing who we work with, how we work, and even how we think about technology. But before that happens in full force, there’s a vital cog that needs to be put into place: edge computing. This article will break […]
Introduction Machine learning is a branch of artificial intelligence that gives computers the ability to learn without being explicitly programmed. Machine learning algorithms build a model from existing data, and then make predictions based on new data. This guide will give you the information you need to understand what machine […]
Introduction Machine learning, like any other type of learning, is not a single entity. There are different ways in which it can be done and each one requires a different approach and skillset. In this blog post, I’ll explore some of the common types of machine learning algorithms (supervised, unsupervised, […]
Introduction Today’s businesses need to track data and make decisions quickly. This means they need access to the latest information in real time, no matter where that information is stored. Traditional cloud computing models are built around storing all of your data in one centralized location based on what’s most […]
Introduction In the past few years, there has been a lot of talk about “the edge.” You may have heard it in discussions about autonomous vehicles and smart cities. But what is edge computing, exactly? How did we get here? And where are we going next? I’m glad you asked! […]
Introduction Data preparation is a critical part of machine learning and big data analysis. It’s what happens before you try to use your data in a model or analysis. The goal is to get the most value from your data by addressing issues that could prevent it from working well […]
Introduction The ability to scale and elasticity are key characteristics of cloud computing. Without these, a service is simply not viable. Given the importance of these two variables, it makes sense to attempt to predict their values in advance. In this post, we’ll examine how you can use the data […]
Introduction Supervised machine learning is an approach to building predictive models that leverages labeled training data. It’s different from the other approaches we’ve covered here because rather than trying to build a model from scratch, supervised learning uses existing data sets with labels (or classifications) already attached. For example, you […]
Introduction Unsupervised learning is one of the most exciting new tools in machine learning. It’s used to analyze your existing data, without any additional labels or keywords. Unsupervised Learning is no longer a new tool Unsupervised learning is not a new tool. It’s been around for decades and has been […]