Machine Learning

Machine Learning enables computers to tackle tasks that have, until now, only been carried out people. Revolutionise Technology builds and deploys machine learning models using tools that meet your needs, helping you solve complex business problems by facilitating data-based decision making. Techniques like computational intelligence, pattern recognition and predictive analysis to create future-ready ML-based applications.

What is Machine Learning?

 At a very high level, machine learning is the process of teaching a computer system how to make accurate predictions when fed data.

Those predictions could be answering whether a piece of fruit in a photo is a banana or an apple, spotting people crossing the road in front of a self-driving car, whether the use of the word book in a sentence relates to a paperback or a hotel reservation, whether an email is spam, or recognizing speech accurately enough to generate captions for a YouTube video.

The key difference from traditional computer software is that a human developer has not written code that instructs the system how to tell the difference between the banana and the apple.

Machine learning feeds a computer data and uses statistical techniques to help it “learn” how to get progressively better at a task, without having been specifically programmed for that task, eliminating the need for millions of lines of written code. Machine learning consists of both supervised learning (using labeled data sets) and unsupervised learning (using unlabeled data sets).

Types of Machine Learning Services

Deep Learning

Deep learning is a type of machine learning that runs inputs through a biologically inspired neural network architecture. The neural networks contain several hidden layers through which the data is processed, allowing the machine to go “deep” in its learning, making connections and weighting input for the best results. This unleashes vast opportunities for businesses and deliver precise solutions to save costs.

Predictive Analytics

Predictive Analytics is the analysis of historical data as well as existing external data to find patterns and behaviors. Predictive analytics model capture relationships among many factors to assess risk with a set of conditions to assign a score, or weightage. By successfully applying this model, businesses can effectively interpret big data for their benefit as seen in various industry such as financial services, marketing, telecommunications, travel, healthcare, etc

Machine Learning Programming

Machine Learning Programming builds custom leaning software to create actionable decision models and automate business processes. Raw data are transformed from big data providers and legacy software systems into clean datasets to execute classification, clustering and regression and deploy models across systems.


Optimization is the most essential ingredient in the recipe of machine learning algorithms. It starts with defining some kind of loss function/cost function and ends with minimizing it, using one or the other optimization routine. The choice of optimization algorithm can make a difference between getting a good accuracy in hours or days. The applications of optimization are limitless and is widely researched topic in industry.

Market Automation solutions

Market Automation solutions break down market segmentation, execute precision marketing, optimize demand forecasting, quantify leads and enhance content recommendations for market segments and specific customers. This is done by integrating machine learning programs with marketing automation and CRM applications.