Artificial intelligence and Machine learning

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Artificial intelligence and machine learning are the part of computer science that are correlated with each other. These two technologies are the most trending technologies which are used for creating intelligent systems.

Although these are two related technologies and sometimes people use them as a synonym for each other, but still both are two different terms in various cases.

Deep Learning

A technique that focuses on teaching computers to learn by example using algorithms similar to cerebral neural network structures and functions.

Machine Learning

Allows the creation of self-sustainable systems that learn from data, identify patterns, and improve with experience and requiring minimal human intervention.

Natural Language

Branch of AI that analyzes human language and helps machines understand and interpret it.

Dialogue Systems

Systems capable of verbal interaction with humans and possessing both input and output channels.

Audio Processing

Enables machines in the recognition and translation of a spoken language into text. Users control machines via speech.

Data Modeling

We create a custom AI model specifically for the engineering and business needs of your enterprise. The system is then trained to conduct an operational analysis.

Knowledge Engineering is an essential part of AI research. Machines and programs need to have bountiful information related to the world to often act and react like human beings. AI must have access to properties, categories, objects, and relations between all of them to implement knowledge engineering. AI initiates common sense, problem-solving and analytical reasoning power in machines, which is much difficult and a tedious job.


Artificial intelligence is a technology that enables a machine to simulate human behavior.

The goal of AI is to make a smart computer system like humans to solve complex problems.

Accurate Output

The goal of ML is to allow machines to learn from data so that they can give accurate output.

Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.


The main applications of machine learning are Online recommender systems, Google search algorithms, Facebook auto friend tagging suggestions, etc.

Machine learning can also be divided into mainly three types are Supervised Learning, Unsupervised Learning, and Reinforcement Learning.

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