AI vs ML vs DL vs DS
Artificial Intelligence (AI) — It’s the broader field in which the aim is to programme machines to somewhat mimic the cognitive processes associated with humans, things such as learning and problem solving.
Machine Learning (ML) — It’s the subsection of Artificial Intelligence. More precisely, Machine learning is the implementation. It uses algorithms to parse data, learn from that data, and make informed decisions based on what it has learned.
Machine Learning itself is commonly broken up into 3 “Types” of learning:
Supervised Learning
Unsupervised Learning
Reinforcement Learning
Deep Learning (DL) — It’s a subset of algorithms and techniques within the area of Machine Learning specifically those utilizing multi-layered Neural Networks algorithms based loosely on the workings of our own brains. These techniques are often more adept at solving problems in more abstract data such as images, sound, and language.
Data Science (DS) — It’s a field that combines these areas, plus mathematics & statistics , programming skills and domain knowledge. It’s summarizes or extract insights from data (exploratory data analysis) and make predictions from large datasets (predictive analytics).
