Artificial Learning Vs. Machine Learning: CA Kunal Bhutada


Artificial Learning Vs. Machine Learning: CA Kunal Bhutada

About The Author

CA Kunal Bhutada


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 the two different terms in various cases.

On a broad level, we can differentiate both AI and ML as:

AI is a bigger concept to create intelligent machines that can simulate human thinking capability and behavior, whereas, machine learning is an application or subset of AI that allows machines to learn from data without being programmed explicitly.

Machine learning is like a child who learns from the behavior of people and surrounding around him. We can say “Jaisadekhawaisasikha”& accordingly sets a pattern.

& Artificial Intelligence is like a young boy we can say mature one who can take decision on the basis of his own intellect. We can say “khud ka dimaglagaya”.

Artificial Intelligence:

Artificial intelligence is a field of computer science which makes a computer system that can mimic human intelligence. It is comprised of two words Artificial and intelligence, which means “a human-made thinking power.” Hence, we can define it as,

Artificial intelligence is a technology using which we can create intelligent systems that can simulate human intelligence.

The Artificial intelligence system does not require to be pre-programmed, instead of that, they use such algorithms which can work with their own intelligence. It involves machine learning algorithms such as Reinforcement learning algorithm and deep learning neural networks. AI is being used in multiple places such as Siri, Google’s AlphaGo, AI in Chess playing, etc.

Based on capabilities, AI can be classified into three types:

  • Weak AI
  • General AI
  • Strong AI


Machine learning is about extracting knowledge from the data. It can be defined as,

Machine learning is a subfield of artificial intelligence, which enables machines to learn from past data or experiences without being explicitly programmed.

Machine learning enables a computer system to make predictions or take some decisions using historical data without being explicitly programmed. Machine learning uses a massive amount of structured and semi-structured data so that a machine learning model can generate accurate result or give predictions based on that data.

Machine learning works on algorithm which learn by its own using historical data. It works only for specific domains such as if we are creating a machine learning model to detect pictures of dogs, it will only give result for dog images, but if we provide a new data like cat image then it will become unresponsive. Machine learning is being used in various places such as for online recommender system, for Google search algorithms, Email spam filter, Facebook Auto friend tagging suggestion, etc.

                          Google Search Engine                                                                           Email Spam Filter        


                                   Facebook Auto Tagging Suggestion

It can be divided into three types:                                                                                                                                                     #Supervised learning               #Reinforcement learning         #Unsupervised learning


Difference Between Artificial Intelligence & Machine Learning:


Sr. No.

Artificial Intelligence Machine Learning
1. Artificial intelligence is a technology which enables a machine to simulate human behavior.


Machine learning is a subset of AI which allows a machine to automatically learn from past data without programming explicitly.
2. The goal of AI is to make a smart computer system like humans to solve complex problems.


The goal of ML is to allow machines to learn from data so that they can give accurate output.
3. In AI, we makeintelligent systems to perform any task like a human. In ML, we teach machines with data to perform a particular task and give an accurate result.
4. Machine learning and deep learning are two subset of artificial intelligence. Deep learning is main subset of machine learning.
5. AI is working to create an intelligent system which can perform various complex tasks.


Machine learning is working to create machines that can perform only those specific task for which they are trained.
6. AI system is concerned about maximizing the chances of success. Machine learning is mainly concerned about accuracy and patterns.
7. On the basis of capabilities, AI can be divided into three types, which are, Weak AI, General AI, and Strong AI.


Machine learning can also be divided into mainly three types that are Supervised learning, Unsupervised learning, and Reinforcement learning.
8. It includes learning, reasoning and self-correction.

It includes learning and self-correction when introduced with new data.



Income Tax Act on Your Mobile Now Android Application For Income Tax Act – 1961 with Cost Inflation Index and other tools on Mobile now at following link:




Whatsapp Group at