Machine Learning In The Cloud With Azure Machine Learning
The history of data science, machine learning, and artificial Intelligence is long, but it’s only recently that technology companies - both start-ups and tech giants across the globe have begun to get excited about it… Why? Because now it works. With the arrival of cloud computing and multi-core machines - we have enough compute capacity at our disposal to churn large volumes of data and dig out the hidden patterns contained in these mountains of data.
This technology comes in handy, especially when handling Big Data. Today, companies collect and accumulate data at massive, unmanageable rates for website clicks, credit card transactions, GPS trails, social media interactions, and so on. And it is becoming a challenge to process all the valuable information and use it in a meaningful way. This is where machine learning algorithms come into the picture. These algorithms use all the collected “past” data to learn patterns and predict results or insights that help us make better decisions backed by actual analysis.
You may have experienced various examples of Machine Learning in your daily life (in some cases without even realizing it). Take for example
Credit scoring, which helps the banks to decide whether to grant the loans to a particular customer or not - based on their credit history, historical loan applications, customers’ data and so on
Or the latest technological revolution from right from science fiction movies - the self-driving cars, which use Computer vision, image processing, and machine learning algorithms to learn from actual drivers’ behavior.
Or Amazon's recommendation engine which recommends products based on buying patterns of millions of consumers.
In all these examples, machine learning is used to build models from historical data, to forecast the future events with an acceptable level of reliability. This concept is known as Predictive analytics. To get more accuracy in the analysis, we can also combine machine learning with other techniques such as data mining or statistical modeling.
This progress in the field of machine learning is great news for the tech industry and humanity in general.
But the downside is that there aren’t enough data scientists or machine learning engineers who understand these complex topics.
Well, what if there was an easy to use a web service in the cloud - which could do most of the heavy lifting for us? What if scaled dynamically based on our data volume and velocity?
The answer - is new cloud service from Microsoft called Azure Machine Learning. Azure Machine Learning is a cloud-based data science and machine learning service which is easy to use and is robust and scalable like other Azure cloud services. It provides visual and collaborative tools to create a predictive model which will be ready-to-consume on web services without worrying about the hardware or the VMs which perform the calculations.
The advantage of Azure ML is that it provides a UI-based interface and pre-defined algorithms that can be used to create a training model. And it also supports various programming and scripting languages like R and Python.
Learn how to design, deploy, configure and manage your machine learning models with Azure Machine Learning : https://bit.ly/2sXuBTY