Predictive analytics involves applying a wide range of machine learning algorithms to gain predictive power. It is more or less synonymous with machine learning, the most popular and widespread variant of AI, comprised of a set of algorithms that learns to model data by observing large chunks of it. Predictive algorithms or machine learning is used by startups to big corporations today to make use of large amounts of data they gather and generate everyday. Predictive ability is obtained through sophisticated modeling of data and key to success is applying right algorithm to solve right problem. This decision depends on multiple factors such as data volume, type, velocity and also the specific problem you are trying to solve with machine learning. Here, we help you not only by guiding you to pick right tools but also by building solutions with powerful predictive capabilities.
Deep learning is a subset of machine learning that utilizes neural networks with many hidden layers, hence the deep. It has a history of over 50 years but recent high availability of data and computational resources made real world applications of deep learning possible and successful. Deep learning is the underlying technology behind most of the notable applications from Apple Siri (intelligent assistant) to Tesla Autopilot (autonomous driving). With large amounts of right data deep learning can deliver high predictive power and understanding of complex and unstructured data types such as natural language, images and video. It may require significant computational resources specially on large datasets, thus considering deep learning as a silver bullet can be an overkill unless you make the right choice.
Modern day computer vision is a powerful crossover of traditional computer vision and deep learning. It focuses on analysing image and video content that have become widespread with the emergence of social media and consumer devices that can produce rich multimedia content. Computer vision has become immensely helpful in analysing these rich data types. It can be used to perform many tasks ranging from simple object recognition to more sophisticated applications such as virtual fitting room. Yet most of the multimedia content that can be used to generate valuable insights is thrown away unanalysed today, one of the best examples being CCTV video footage. We add value to your business by identifying and analysing right multimedia content using our powerful computer vision stack.
Human-like natural language understanding is sometimes considered as the holy grail of AI. Human languages are inherently complex for machines. Yet if we are to analyse and understand large amounts of data generated by humans (in natural language) everyday, we need AI technology to decipher that data into a machine-understandable form. The emergence of advanced NLP techniques and deep learning have made this possible, best examples being chatbots and intelligent assistants. NLP gives you the ability to interact better with your customers and understand them better, which eventually brings competitive advantage to domains ranging from marketing to healthcare. We offer a wide range of NLP capabilities to transform your data into insights no matter which domain you are from.