If you are new to data science, this title is not intended to insult you. It is my second post on the theme of a popular interview question that goes something like: “explain [insert technical topic] ...

Machine learning is a branch of computer science that teaches computers to 'learn' patterns from data instead of being programmed step by step. Think of it like this: instead of telling a computer ...

AI can be called a superset of Machine Learning (ML) processes and Deep Learning (DL) processes. AI is usually an umbrella term used for ML and DL. Deep Learning is again a subset of ML (see image ...

AI (Artificial Intelligence) is a broad concept and its goal is to create intelligent systems whereas Machine Learning is a ...

We have explained the difference between Deep Learning and Machine Learning in simple language with practical use cases.

John Mueller from Google gave one of the clearest and easiest to understand explanations on how Google uses machine learning in web search. He basically said Google uses it for "specific problems" ...

Machine-learning models can make mistakes and be difficult to use, so scientists have developed explanation methods to help users understand when and how they should trust a model's predictions. These ...

At the core of reinforcement learning is the concept that the optimal behavior or action is reinforced by a positive reward. Similar to toddlers learning how to walk who adjust actions based on the ...