AI ,ML ,DL, Data Science is everything the same ? 🤷♀️lets check them out😃
Hey folks, confused about different terms related to AI ,I guess then you are at the right place , because here is your little who is ready to explain all terms in simple manner.
Few months back I started my journey in Data Science, I was in the similar situation where all these buzzing words came into my mind and made me really confusing , so now I would try make these terms into meaningful for you all….So let’s start…..
Artificial Intelligence:
firstly… .AI is very very vast, I mean AI is a complete set with all the ML,DL,DS topics in it.
“ A branch of computer science dealing with the simulation of intelligent behavior in computers.” — Merium-webster
Whenever we try try to use other techniques like ML,DL,DS our final goal would be to built an AI application.
for example lets consider Netflix ,in Netflix we have a feature of recommendation system which can be a part ML or DL .So whenever some one asks what is Netflix we would say it as an AI app, it may consists different features but end of the day it’s an AI app
So basically AI is creating machines to make it’s own decisions without any human intervention.
Machine learning :
Machine learning is mainly a subset of AI .
Basically in Machine Learning we use many statistical tools to analyze, and to do different tasks on the given data. These tasks may include predictive modelling which is trying to predict future events by data patterns.
Machine learning is the science (and art) of programming computers so they can learn from data,” writes Aurélien Géron in Hands-on Machine Learning with Scikit-Learn and TensorFlow.
The whole Machine Learning is mainly comprised of three types ,they are
- Supervised learning:
- Unsupervised learning:
- Reinforcement learning:
We may go in detail about them in future blogs but let’s just Understand what they are basically
- Whenever the Data we have got is Labelled(we have given the output data)then it is considered into supervised machine learning .Here we use Regression and classification algorithms.
- Whenever the Data provided is not labelled the its considered into Unsupervised machine learning, here we are use Clustering algorithms.
- Reinforcement machine learning also known as semi supervised machine learning works initially with the labelled data then after it tries to learn itself. Netflix mainly use this technique.
Deep learning:
Now lets look at Deep learning which growing very fast now-a-days, it is a subset of Machine learning which tries to mimic human brain in the form of neurons.
Generally, when we see a dog with our eyes ,the signal then passes through the neurons present in our brain and while passing ,the data which has been seen will been preprocessed and finally we visualize the dog image. In the similar way, scientists in early 90’s taught about the idea to try to implement similar neural network on machines ,that’s when the perceptron was introduced .After that there have various contribution have been done to DL field.
DL mainly has 3 neural networks they are:
- Artificial neural network
- Convolution neural network
- Recurrent neural networks
Data Science:
Finally here we are Data Science the boom of the 21th century …
We can say that ,Data science is the field of study that combines domain expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Here Data science practitioners apply machine learning or deep learning algorithms to numbers, text, images, video, audio, and more to produce Artificial Intelligence systems which perform tasks that require human intelligence.
Conclusion:
lastly I would thank you all for going through my first blog post ,although it’s just a basic info about all the terms but I think it would be a great help to all the newbies out there who are confused in these terms.
And please leave your comments so that I could be improving myself and try to give best content possible — — — — — — — — — Sai prakash
