Machine Learning is a sub-category of AI, and Deep Learning is a sub-category of ML, meaning they are both forms of AI.

Artificial Intelligence (AI) can be understood as an umbrella that consists of both Machine learning and deep learning. Or We can say deep learning and machine learning both are subsets of artificial intelligence.

What is Artificial Intelligence (AI)?

Artificial Intelligence is defined as a field of science and engineering that deals with making intelligent machines or computers to perform human-like activities.

Types of Artificial Intelligence

AI can be categorized mainly into 4 types as follows:

1. Reactive machine

2. Limited memory

3. Theory of Mind

4. Self-awareness

Application of Artificial Intelligent

• Language Translations

• AI in healthcare

• Speech recognition, text recognition, and image recognition

• AI in astronomy

• AI in gaming

What is Machine Learning?

Machine Learning is defined as the branch of Artificial Intelligence and computer science that focuses on learning and improving the performance of computer machines through past experience by using algorithms.

Types of Machine Learning

Supervised Machine Learning
This type of ML method uses labeled datasets to train machines and, based on these datasets, machines predict the output.

Supervised machine learning can be further categorized into 2 types of problems as follows:

• Classification

• Regression

Unsupervised Machine Learning
Unsupervised machine learning is just the opposite of supervised learning. Unlike supervised machine learning, it does not need supervision, which means it does not require labeled datasets to train machines.

Unsupervised machine learning is further categorized into two types:

• Clustering

• Association

Semi-supervised Machine learning
Semi-supervised learning is the combination of both supervised and unsupervised machine learning. Although it uses both labeled and unlabelled datasets to train models and predict the output, mostly, it contains the unlabelled datasets

Reinforcement Learning
Reinforcement learning is defined as the feedback-based method to learn from past experience and improve the performance of models. In this method, an AI agent automatically explores its surroundings by hitting and trying actions

What is Deep Learning?

"Deep learning is defined as the subset of machine learning and artificial intelligence that is based on artificial neural networks".

Deep Learning is a set of algorithms inspired by the structure and function of the human brain. It uses a huge amount of structured as well as unstructured data to teach computers and predicts accurate results.

The main difference between machine learning and deep learning technologies is of presentation of data. Machine learning uses structured/unstructured data for learning, while deep learning uses neural networks for learning models.

Types of deep neural networks

There are some different types of deep learning networks available. These are as follows:

• Feedforward neural network

• Radial basis function neural networks

• Multi-layer perceptron

• Convolution neural network (CNN)

• Recurrent neural network

• Modular neural network

• Sequence-to-sequence models

Text Similarity Measures.