Free Articles, Free Web Content, Reprint Articles
Monday, July 13, 2020
 
Free Articles, Free Web Content, Reprint ArticlesRegisterAll CategoriesTop AuthorsSubmit Article (Article Submission)ContactSubscribe Free Articles, Free Web Content, Reprint Articles
 

What is the Difference Between AI, ML, Statistics and Data Mining?

Know the difference between Artificial intelligence, machine learning, statistics, and data mining. It helps the organization in knowing how exactly the garnered dataset will be useful to them. Statistics is one of the most fundamental fields of study in mathematics that forms the base of the study for other computer science fields like Machine learning, Artificial Intelligence, etc.

In a world full of ignorance, we must not forget to do some reality check regularly. Having proper
knowledge of the topics that are a frequent trend gives us the power to determine how the
world is growing. Some of the regularly misinterpreted and misunderstood terms today are
Artificial Intelligence, Machine Learning, Statistics, and Data Mining. if you are searching for the best machine learning course search in Delhi. you are the right place in the best Machine Learning Course in Delhi

Not denying the fact that these topics are not completely different from each other but there
exists a thin line that separates each of them. Each being closely related to the fields of
mathematics and computer science, these topics are the steps towards a smarter tomorrow
we’ve been waiting for.
Data mining, machine learning, artificial intelligence, and statistics are all inter-related studies
that are inspired by each other. The difference arises in their application as well as a way of using
each of them. In order to understand the difference between them, we should first look into
what each of them actually is.


Data Mining


As the name suggests, Data mining is involved with an in-depth analysis of huge datasets that
are available to find relations and patterns. The field of Data mining is most prevalent in business
analytics sectors, stock markets, for improving sales, developing strategies, etc. It helps the
organization in knowing how exactly the garnered dataset will be useful to them. One of the
major advantages of data mining is that it understands which set of data is useful and relevant,
and further work on that to make the required task a success. Retail, manufacturing, education,
banking sectors are all using data mining today to boost their business models and produce
better outcomes.


Statistics


Statistics is one of the most fundamental fields of study in mathematics that forms the base of
the study for other computer science fields like Machine learning, Artificial Intelligence, etc. This
field of math is involved with an experimental set of data as well as real-world data, and it finds
out ways to study both of them by using different measures like mean, variance, correlation
coefficient, skewness, distribution, testing, etc. Statistics is the heart of any business model. No
model can be created without making use of statistics as it helps to analyze and structure
required as well as the available information.


Machine Learning


Machine Learning is one step higher in the department of computer science and works around
teaching machines how to give outputs based on the previous input that was fed to it. Machines
don’t learn but memorize with experience. They’re trained with an algorithm on a training set.
The model is then evaluated with evaluation metrics and checked for accuracy. It is then tested
on a testing dataset or an unknown dataset to check if the model works properly. This is how a
machine learns and applies whatever it has learned on unknown datasets. A number of
algorithms are used in machines based on the required problem statement. These algorithms are

highly classified into 3 sections, Supervised Learning, Unsupervised Learning, and Reinforcement
Learning.


Artificial Intelligence


The topmost layer after Deep Learning and Machine Learning is Artificial Intelligence. Artificial
intelligence is the more complex version of Machine Learning involved with building such
technologies that have the capacity and capability of performing such computations that require
human intelligence. Simply speaking, it builds machines that work like humans. This field is
literally changing the world. It has and is still making an impact in almost every sector of the
world. This field is currently being used mostly in facial recognition systems, speech recognition
systems, security systems, gaming, agriculture, etc.


Difference between Machine Learning, Artificial Intelligence, Data Mining and Statistics

Since we now know what each of these fields means, we can delve deeper into knowing what the
difference between all of these is. Statistics is the field of study related to mathematics while the
rest of them belongs to Computer Science. Even though statistics is not a computer science
field, it still forms the base of study for any statistical field here.
Machine learning, data mining and artificial intelligence are all based on statistics. The main aim
of these fields is to find a relation between different datasets and models given to them which is
the fundamental of statistics. The statistical measures help us in understanding any model
correctly.


The difference between the remaining three fields, Machine learning, artificial intelligence, and
data mining is closely related. They are arranged as follows:


Data Mining <= Machine Learning <= Artificial Intelligence


Data mining will always be the base as it is related to the preprocessing of datasets that will be
used for building models in machine learning and Artificial intelligence. Hence, data mining
revolves around playing with big data and looking out for relations or patterns among them,
doing research in related fields, etc. Machine Learning and Artificial intelligence though seem to
be similar are actually very different techniques. While Machine learning means making the
machine learn how to execute similar tasks based on previous experience, Artificial intelligence
deals with creating a simulation of human behavior.

Machines are not learners, they are memorizers. They are fed an input, an algorithm, and a
testing set. They memorize what they are supposed to do in case of such datasets and they
perform. In the case of Artificial intelligence, machines are still memorizing and using machine
learning techniques but on a higher note, and are making advancement. These machines are now
behaving like humans. Artificial intelligence lies on top of the 3 layered diagrams consisting of
deep learning, machine learning and AI itself. PythonTraining.net’s Machine Learning course in Delhi will simply help you gain expertise in machine learningScience Articles, a kind of AI that automates big data analysis to adapt and learn with experience to perform certain tasks without complete programming.


Conclusion


This is exactly how these topics are so closely related yet so different. Today’s world and the
The future is a gift of machines that are making our lives much easier and accessible.

Source: Free Articles from ArticlesFactory.com

ABOUT THE AUTHOR


Hi,

I am yeswardhan, I am a Content Writer For Machine Learning, Data Science, Digital Marketing, Artificial Intelligence ect. 



Health
Business
Finance
Travel
Technology
Home Repair
Computers
Marketing
Autos
Family
Entertainment
Education
Law
Communication
Other
ECommerce
Sports
Home Business
Self Help
Internet
Partners


Page loaded in 0.247 seconds