Ai vs Machine Learning vs Deep Learning: What's the difference

You probably have heard the terms Artificial Intelligence,Machine learning and Deep learning on Internet or an advertisement of smartphone.Many of the smartphone brands features  AI charging,AI face ID and AI photos.You might have seen universities conducting machine learning programs.It is important to know the difference among these.The technology has developed a lot it's is not like earlier what we program to machine and is giving it's results.The technology has came to such an extent that even machines can develop learning and think like humans.We have made a detailed study of all of these.Stick to end of this article to find out the difference between AI vs Machine Learning vs Deep Learning.

What is Artificial Intelligence

Just like humans machines exhibits intelligence known as Artificial Intelligence.Machines are  developed in way to think and react like humans.The actual term 'Artificial Intelligence' was first coined in the year 1956 and gained it's popularity these days.With the use of AI it is possible for machines to learn and process things using large amount of data and learning from experiences.Artificial Intelligence it self is very huge there are various subset's which we will be learning further in this blog.Real life examples of Artificial Intelligence is Amazon echo,Alexa etc.

What is Machine Learning

It is the subset of Artificial Intelligence.It is way for machines to make decisions using input data.Machine learns from experiences we have to give data to machines from which machine recognizes and understand various patterns and make decisions according to it.For example first you have to give lots of images of birds So that the machine will understand it is a bird.Then training part comes in where you have to give picture of another bird and check how accurate it is working. Real life examples of Machine learning are email spamming.When there are keywords present in email like bitcoin transaction it will automatically put it into the spam folder.

Types of Machine Learning

1.Supervised Learning

It is a type of learning in which you have to give labelled inputs to the machine and machine will train according to these labelled inputs.It simply means that it can predict outcomes using past data.In this type both inputs and outputs has to be given for learning.This type of learning is used to solve problems based on regression and classification.For example detecting spamming emails by checking keywords like bitcoin or if it is given many pictures of animals  monkeys,tigers in the memory and asked if this is a picture of monkey or not then it can give the output using previous data or measuring weights.

2.Unsupervised Learning

It is a type of learning in which you don't have to provide data to the machine it will identify certain hidden patterns,images,text and diagrams using this type of learning.Similarities and differences are separated  using given data and from these similarities it produces the output.This type of learning is used to solve problems based on association and clustering.An example of unsupervised learning is detecting credit card frauds or recommendations by Netflix or YouTube.

3.Reinforcement Learning

It is a type of learning in which machine learns using trail and errors and discovering risks and rewards.Systems are given no training in this reinforcement learning.Using this type of learning increases the efficiency of machines.No predefined data is given here.An example of Reinforcement learning is robot.When you leave the robot it will gather information from user and learn by giving rewards if he is right or punishment if he is wrong or self driving car.

What is Deep learning

It is a subset of Machine learning.It is the way to mimic human brain using algorithms.It works exactly as the human brain.Just like our human brain sends and receive signals using biological neurons same goes with the deep learning .Artificial neurons sends and receive signals using input and output layers.There are total three layers in artificial network layer that is input layer,hidden layer and output layer.All the inputs are received in the input layer,all the processing is done in the hidden layer and out is passed through the output layer.

Artificial Neural Network

As you can see in the above image.This is called as artificial neural network.for example how to know whether the object is square or not it will check all the parameters such as where all sides are equal,it is a closed figure,all sides are perpendicular,all sides are parallel,there are in total 4 sides.After checking all the parameters it will confirm that the object is a square.Real life examples of Deep learning are sortie and chatbots which responds to the user as per the input given.

Machine Learning vs Artificial Intelligence

• Machine learning is something that works learns from given data whereas Artificial Intelligence is mostly decision making.
• Machine learning is mainly focused on accuracy whereas Artificial Intelligence is focused on success.
• Machine learning deals with structured data whereas the Artificial Intelligence deals with learning and self correction.

Machine Learning vs Deep learning

• More the data better the deep learning will perform whereas less the data better the Machine learning will perform.
• Since deep learning checks out various parameters it requires better hardware with high end processors and graphic cards but it is not the same in machine learning you can compromise hardware to work with machine learning.
• Deep learning takes more time to train because it deals with larger data and Machine learning takes less time to train because it deals with less data.
• Execution time is less in deep learning whereas it is more in machine learning.
• Interpretability  is very difficult in deep learning we cannot interpret the result properly how the network actually worked but in case of machine learning it is easy to under the logic and reason behind the algorithm.