Explainable AI

By 2022, 75 percent of new end user solutions leveraging AI and ML techniques will be built with commercial instead of open-source platforms. AI and ML solutions will be applied in every business irrespective of their product. So, it’s important to know what the ML algorithm is doing behind the scenes and it’s the duty of the ML engineer to explain the model to the person who is using it. For example, if a model suggests the user the best route then user should be aware of the features and constraints the model is considering to show the best route, so that user has an overview of the whole process and this what explainable AI is....


Tackling Duplicate Data

As the amount of data collected in the world increases, so are the problems related to it! ...


Application of Data Science and AI in Cricket

Big data has taken over the globe from Facebook and Amazon to its use in sports. The use of data analytics in sports is not a new concept. It was brought to the mainstream in the famous novel, Moneyball, which detailed the use of statistics and AI in American baseball. It even became a hit Hollywood movie. ...