SANJITA SRINATH

1. Data science focuses on utilizing data to deliver a company value (cash, development, prestige, etc.).
2. Making predictions and inferences from data that is tailored to the company is the goal of machine learning.
3. The goal of artificial intelligence is to give robots decision-making abilities similar to those of humans.

Machine learning (ML) aims to construct machines that are only capable of performing the specific tasks for which they have been trained, but artificial intelligence (AI) aims to create an intelligent system that can execute a variety of complicated activities. AI is a subset that gives systems the capacity to autonomously learn from experience and advance without being explicitly designed. The fundamental idea is to create algorithms that can take input information and use statistical models to forecast an output, updating outputs as new information becomes available.

in business, ML ≈ AI

A data scientist collects data from many sources and uses machine learning, predictive analytics, and sentiment analysis to glean important information from the data sets he or she has gathered.

To sum it up…

Simply put, Machine Learning is a subset of Artificial Intelligence, while Deep Learning is a subset of Machine Learning. How this works is Deep Learning consists of Neural Networks that calculate an A → B output. Data Science as a whole is so to say a cross-section subset. It consists of AI, ML, and Deep Learning, but has an output of actionable insights. On the other hand, AI, ML, and Deep Learning are focused on building models that can learn by itself using data.