Machine Learning & AI

Innovate and explore new opportunities in your field with our machine learning NLP consulting and development services.

Human language is complex and diverse. We have so many spoken and written languages with its own dialects, syntax rules and slang, both verbally and in writing. The same languages these days we are trying to teach machines as everyone needs their machines to talk. Natural Language Processing combines Artificial Intelligence (AI) and computational linguistics so that computers and humans can talk seamlessly. In Natural Language Processing, the machine learning training algorithms study millions of examples of text - words, sentences, and paragraphs - written by humans. By studying the samples, the training algorithms gain an understanding of the "context" of human speech, writing, and other modes of communication. This training helps NLP software to differentiate between meanings of various texts.

• Automatic Summarization - Intelligently shortening long pieces of text
• Sentiment Analysis - gain positive, negative or neutral opinion from the text or speech to gain insights. This can further probe into the responses how audience has reacted to the speech and who it is being looked at holistically.
• Speech Recognition - recognize and transform spoken language into text, translate or act upon the recognition.
• Topic Segmentation - Automatically classify and divide text, speeches, recordings into coherent segments and is used in improving information retrieval or speech recognition.
• Named entity recognition - Locate and classify named entities pre-defined categories like location, person names, organizations, etc.

Making machines see what humans do

Changing world dynamics has forced humans to preserve time and let machines do what humans can do. Computer vision enables machines to discover meaningful information from digital images and videos and take the next best action based on the information so discovered. Computer vision is used in multiple industries ranging from manufacturing, logistics, automotive, energy and utilities to retail and banking. It is expected to reach USD 48.6 billion by 2022.

What's standing in the way of translating video into real-time actionable insights, however, is managing the volume, velocity and variety of data, as well as connecting the dots on that data. From health care to automotive to manufacturing, computer vision has made great strides to solve real-world problems Data-driven organizations are now deploying prescriptive solutions that are driving tangible benefits, outcomes and near real-time actionable insights. As these solutions become more adaptive, they will bring dramatic improvements to the performance of systems and automated processes, as well as decision making. And that's when a real-time continuous improvement loop will be possible, where a model is constantly retraining itself.