 "An exciting era for computer technology")
One has often wondered about the marvels of technology. Its speed, precision, uniformity and ease in accessibility has transcended from age-old PCs to the contemporary handheld devices. However, what if we told you that this progression was a gradual, expected phenomenon and we are yet to witness more fascinating capabilities of technology!
Till date, computers performed according to programs and applications created specifically for conducting a particular task. To cite a simple illustration, we are able to copy images from the web and edit it to our taste by using platforms such as MS Picture Manager or Paint or Adobe Photoshop. What if computers, like humans, began learning from experience? And this has already begun to take shape.
Machine learning is the dawn of an exciting new era, where computers can figure out how to perform important tasks by generalising from examples.
Machine learning is based on algorithms that can learn from data without relying on rules-based programming. It came into its own as a scientific discipline in the late '90s, as steady advances in digitisation and cheap computing power enabled data scientists to stop building finished models and instead train computers to do so.
Machine learning is linked to artificial intelligence (AI), the development of computers with skills that traditionally would have required human intelligence, such as decision-making and visual perception. It is the part of AI that actually works. You can use it to train computers to do things that are impossible to programme in advance. Search engines like Google and Bing, Facebook and Apple's photo tagging application and Gmail's spam filtering are everyday examples of machine learning. The fundamental goal of machine learning is to generalise beyond examples in the training set.
Two facets of mechanisation should be acknowledged when considering ML in broad terms. Firstly, it is intended that the classification and prediction tasks can be accomplished by a suitably programmed computing machine. Secondly, it is intended that the creation of the classifier should itself be highly mechanised, and should not involve too much human input.
One often believes machine learning to be synonymous with AI, but it isn't so. AI is a broad term referring to computers capable of essentially coming up with solutions to problems on their own. The information needed to get to the solution is coded and AI uses the data to come up with a solution.
On the other hand, machine learning takes the process a step further. It is capable of generalising information from large data sets, and detect and extrapolate patterns to apply the information to new solutions and actions. Machine learning and AI are highly interdependent fields, they need each other to analyse and perform activities. Machine learning is playing a vital role in transforming a variety of industries.
The dynamic nature of the market is a major hurdle for senior management of organisations across verticals. The diversifying trends and evolving consumer preferences are compelling organisations to rely on technology to understand and analyse market situations more accurately.
Today's cutting-edge technology already allows businesses not only to look at their historical data but also to predict behaviour or outcomes. Machine learning is a critical tool used for gaining actionable insight into ever-increasing data. The most common application of machine learning tools is to make predictions and find solutions for problems in a business:
- Making customised recommendations for customers
- Anticipating the future performance of employees
- Forecasting customer loyalty
Machine learning is a fully managed, on-demand, pay-as-you-go and easy to use service provided by prominent cloud providers like Amazon Web Services and Microsoft Azure. The cloud-based machine learning service gives business a chance to get started with it and make valuable decisions.
Harshad Mehendale
Consultant, Blue Star Infotech
Consultant, Blue Star Infotech
