Data Science, Artificial Intelligence and Machine Learning.

 Data Science

Data science is actually a combination of statistics, machine learning, and data visualization. The job of a data scientist is to find answers to some questions through datasets. Details.

Artificial intelligence

Artificial intelligence is a set of problems and problem-solving methods that can be used to solve complex problems. Teaching computers to play cards, chess, natural language translation, security strategy management includes AI. The problem with AI is that it doesn't have to be based on actual datasets, it can be theoretical.

Machine learning

Machine learning is a division of artificial intelligence where intelligent systems are created through datasets or interactive experiences. Machine learning technology is being used in many fields besides Cybersecurity, Bioinformatics, Natural Language Processing, Computer Vision, Robotics.

The most basic part of machine learning is data classification, such as checking whether an e-mail or website comment is spam. Currently, there is a lot of research going on on Deep Learning or Deep Network, mainly Convolution Neural Network is used in these cases.

At present, machine learning is a very important issue at the industrial level. Everyone should know some of the other machine learning methodologies. Several things in machine learning will overlap with data science, but the main target of machine learning is to build predictive models.

At a glance

That is, AI helps build intelligent machines, ML is the AI's subfield that helps the machine learn something, and the latest data science learning algorithm helps the machine to figure out data patterns that it can use in later work.

Data Science, ML, and AI will often feel the same way because there is very little difference between them. But a common joke about data science is,

A data scientist has more computer knowledge than a statistician and his statistical knowledge is more than a computer scientist.