A.I VS ML VS DL VS DS

What is the difference between Artificial Intelligence, Deep Learning, Data Science?

Artificial Intelligence is a vast field and Machine Learning is a subset of Machine Learning and Deep Learning is subset of Machine Learning.

AI was termed by John McCarthy in 1956 where the goal was that machines should pose the ability to learn or understand or deal with new trying situations.

Artificial Intelligence can be split into two branches:

1.Applied AI (weak AI):- to perform specific tasks.

2.Generalized AI (strong AI):- to act like humans.

Deep Learning: - Deep Learning is a subset of Machine Learning where learning method is based on Feature Learning. E.g. To Identify a Dog/Cat from an image it has to learn its features first like tail,ears,etc.

In Deep Learning data goes through multiple numbers of non-linear transformations to obtain an output.

Here Hidden Layer Randomly extract features from the Input Layer and performs feature detection. And the output detected by feature learning is much more accurate than the machine learning model.

Some Renowned examples of Deep Learning are:

谷歌 Lens, Facebook face recognition, etc.

The some of the major differences between Machine Learning and Deep Learning are:

1.Data Dependencies: Deep Learning requires a huge amount of data to get the desired results, whereas it's not the same with Machine Learning, in ML we can get output from very small amounts of data.

2.Hardware Dependencies: Deep Learning requires high-end machines to perform operations especially requires a GPU, while Machine Learning works efficiently on small machines.

3.Execution Time: Deep Learning Algorithm takes more time to execute as compared to Machine Learning.

InShort:

Artificial Intelligence- "Human Intelligence exhibited by machines".

Machine Learning - "An approach to achieve Artificial Intelligence"

Deep Learning - "A technique for implementing machine learning"

Data Science: It is the Art and Science of drawing actionable insights from the data. It is applied in most of the domains like Retail, Bank, E-Commerce, Healthcare and Telecom, etc.

In flow chart of Data Science:

Firstly Data is collected from various data sources, it is preprocessed using various techniques, Insights are drawn from the data, Visualizations are drawn out of them for better understanding and upon these insights Machine Learning/Deep Learning Model is built.