ML and AI

What is ML And AI ?

What does ML and AI mean?

Machine Learning and Artificial Intelligence are creating a huge buzz worldwide. The plethora of applications in Artificial Intelligence have changed the face of technology. These terms Machine Learning and Artificial Intelligence are often used interchangeably. However, there is a stark difference between the two that is still unknown to the industry professionals.

What is Machine Learning ?

Machine learning (ML) is the study of computer algorithms that improve automatically through experience and by the use of data. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as email filtering and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.

Our team excels in developing innovative techniques for your business problems where we strengthen the power of Machine Learning and data sciences to provide best in class end to end Artificial Intelligence based solutions.Here are the few highlights about the projects which we have taken care of under ML and AI.

  • Facial Recognition system
  • Food Category Classification
  • Emotion Recognition System
  • Disease Classification through Chest X-Ray
  • Image Enhancement
  • Face Mask Detector

What Is Artificial Intelligence ?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine that exhibits traits associated with a human mind such as learning and problem-solving. Artificial intelligence (AI) is wide-ranging branch of computer science concerned with building smart machines capable of performing tasks that typically require human intelligence. AI is an interdisciplinary science with multiple approaches, but advancements in machine learning and deep learning are creating a paradigm shift in virtually every sector of the tech industry.

Norvig and Russell go on to explore four different approaches that have historically defined the field of AI:

  • Thinking humanly
  • Thinking rationally
  • Acting humanly
  • Acting rationally

Why is machine learning important?

Resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. Things like growing volumes and varieties of available data, computational processing that is cheaper and more powerful, and affordable data storage. All of these things mean it's possible to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results – even on a very large scale. And by building precise models, an organization has a better chance of identifying profitable opportunities – or avoiding unknown risks.

Working of Virtual Personal Assistants –

Siri (part of Apple Inc.’s iOS, watchOS, macOS, and tvOS operating systems), Google Now (a feature of Google Search offering predictive cards with information and daily updates in the Google app for Android and iOS.), Cortana (Cortana is a virtual assistant created by Microsoft for Windows 10) are intelligent digital personal assistants on the platforms like iOS, Android and Windows respectively. To put it plainly, they help to find relevant information when requested using voice.