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Galyna Chekan
Galyna Chekan

Posted on • Originally published at perfectial.com on

The ABCs of Machine Learning

Machine Learning (ML) gets brought up a lot in major media outlets and blogs but, in most cases, the authors provide very hand-wavy explanations as to how it works. Despite the spotlight being shone on it, the technology is still poorly understood outside of a small circle of practitioners.

So, is machine learning really something your business can integrate immediately to enhance operational efficiency? Or is the seemingly unlimited power of ML just a hyped up tale?

In this post, we’ll explain what Machine Learning is, its benefits, and how you could go about implementing it.

What’s Machine Learning?

What’s Machine Learning?

Machine Learning is a subset of AI that allows systems to “self-educate”. It is a class of algorithms that, when fed data, can learn to make various kinds of predictions without being programmed to do so.

Machine learning has been around for quite a while, but it’s only recently that it started gaining traction in digital business. This is primarily due to the emergence of new database technologies, such as Hadoop, that provided an inexpensive way for corporations to collect massive amounts of data.

The lifecycle of a Machine Learning project resembles the traditional Data Science lifecycle. It consists of:

1) Identifying a business problem

The first thing to do is articulate clearly your project’s objectives and requirements and then translate them into a definition of a data mining problem.

2) Aggregating data

Next, look through various sources (logs, IoT devices, ERP systems, purchased info, etc.,) to collect all the relevant data.

3) Polishing data

Have the raw data cleansed, transformed and normalized so that you can feed it toann ML algorithm.

4) Model planning

Select ML processes that you’ll use for training; tweak and calibrate their parameters to optimal values.

5) Evaluating the model

Double check the ML model(s) you’ve chosen to ensure that no critical business issue has been overlooked; review each step of the model construction.

6) Deploying

Now that the ML process(es) provided you with insights and you have some business-usable results on your hands, it’s time to start deploying them to your enterprise applications or data stores.

Related: How Perfectial helped Ayasdi launch a unique machine intelligence platform that leverages Topological Data Analysis, Big Data, and automation.

Want to learn more about Machine Learning and the benefits it can bring to your business? Contact our expert right now to get a free consultation.

The post The ABCs of Machine Learning: How Your Company Can Use ML to Drive Efficiency appeared first on Software Development Company Perfectial.

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