AyahAnalytics...."Engineering Knowledge with Purpose"

 Introduction  Artificial Intelligence (AI) is all around us, from Netflix recommendations and your banking app to safeguarding yourself against fraudulent transactions. But as AI systems become increasingly complex, one pressing question is absent: Can we rely on them if we have no clue how they work? From there comes Explainable AI (XAI). In the past, traditional AI models were treated as “black boxes” — you put in some input, you get some output, even if you don’t ask too many questions about how the in between happens. But in sensitive sectors like health care, law enforcement and finance, lacking access to the “why” behind a decision can have steep consequences. XAI seeks to open up this black box so we can shed some light on how AI systems arrive at decisions, making them more transparent, accountable, and worthy of our trust.   What is Explainable AI ? Explainable AI (XAI) is a set of techniques and methodologies that enable human users to understand why and wh...

  Introduction to ML and its Applications By Viraj Sanjay Dhadas Roll no- 3072 Div – A   Introduction Have you ever thought that Netflix finds out what you are showing next? Or how your phone can just unlock and unlock your face? Behind these smart properties is a powerful branch of technology called Machine Learning (ML).   Machine changes the learning industries - from the health care system and finance to entertainment and agriculture - the machines from data "learning" to make decisions without clearer. In this blog, we will break what machine learning is, how it works, and it is used in the real world, in all simple, easy -to -understand language.     What is Machine Learning? In the core, machine learning is an area of ​​artificial intelligence (AI) that focuses on the building system that can learn from data, identify patterns and decide with minimal human intervention.   Traditional programming works this way: Y...