AI/ML and
Deep Learning

A Bayesian network is a graphical model representing probabilistic relationships among variables. Introduction Probabilistic models are based on the theory of probability. I guess that was quite self-explanatory, considering it is in the name. Probabilistic models consider the fact that randomness plays a role in predicting future outcomes. The opposite of randomness is deterministic, which tells us that something can

Let’s first understand what the “Theory of Mind” is before we get into what the “Theory of Mind AI” is in the world of Artificial Intelligence. According to Wikipedia, in psychology, the Theory of Mind is as follows: “Theory of Mind refers to the capacity to understand other people by ascribing mental states to them, surmising what is happening in

Overfitting is a typical mistake that many machine learning engineers make, typically beginners. Unfortunately, this mistake can completely ruin your machine learning model, producing incorrect outputs and leading to making the wrong decision.  What is Overfitting in Machine Learning? Overfitting in Data Science occurs when a statistical model fits precisely against its training data. It is a modeling error when

Artificial Intelligence (AI), Machine Learning (ML), and Data Science are very common keywords that we use worldwide today. Irrespective of the profession pursued, these keywords are common across all the domains. Newspapers are covered with articles related to data science or AI on a day-to-day basis. Every day, there is news talking about the advancements in these fields. Technology is

The title ‘Machine Learning Engineer’ has become very popular over the years. Many people enter Data Science and transition to become Machine Learning Engineers. Others are highly educated and experienced and have the right skills. Let’s first start with the definition of a Machine Learning Engineer. A Machine Learning (ML) Engineer is a programmer proficient in researching, building, and designing