AI v/s Deep Learning v/s ML v/s Data Science

Today innovative technologies like artificial intelligence, machine learning, are buzzing everywhere. However, many among us do not understand these concepts fully and that is why we bring to you a comparison between all the contemporary technologies.

We have curated the differences between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and Data Science (DS) for you to have a better understanding of these concepts.

Artificial Intelligence (AI)

Artificial Intelligence (AI) basically means intelligence similar to that of humans demonstrated by machine. It is different from conventional computer programming and it enables computer systems to think and act like human do. It requires machine learning, deep learning and data science to build and AI application.

Machine Learning (ML)

Machine Learning is also known as a subset of Artificial Intelligence. ML helps us to operate with minimal human interference. It can learn from data analysis and make decisions on its own. Moreover, Machine Learning has the capacity to learn on its own and develop with experience over time without too much of manual programming.

Deep Learning (DL)

Deep Learning can be defined as a technology based upon multilayer neural network architecture which mimics the human brain. Deep learning has the following features:

• Artificial neural network (ANN) –which takes inputs in the form of numbers
• Recurrent neural network (RNN) – which involves inputs data such as time series
• Transfer learning – this is an extension of ANN, RNN and CNN
• Convolutional neural network (CNN) – which takes inputs like images

Data Science (DS)

Data Science is an inter-disciplinary concept which uses statistics, numerical optimization, probabilities, differential calculus and linear algebra to understand real phenomena. DS overlaps with artificial intelligence techniques to analyse data.  

AI v/s Deep Learning v/s ML v/s Data Science

Artificial intelligence takes the help of DL, ML and DS to build an AI application. Whereas Machine Learning (ML) involves the use of statistical tools and also includes supervised, unsupervised and reinforced learning. However, when it comes to Data Science (DS), it uses mathematical tools like linear algebra, probabilities among others. As opposed to DS, Data Learning (DL), is a multi-layer neural network which is based on ANN, RNN, and CNN.

What do you know? What have you Learnt?

AI enables operations without manual intervention and as compared to other technologies ML is a subset of AI and it uses data analysis to solve problems. DL is a subset of ML and as opposed to DL, DS uses mathematical tools.