QML Day-1: What is Quantum Machine Learning (QML)? and Why do we need it?
Today is the first day of my 30 days quantum exploration challenge by QuantumComputingIndia and in this article I’ll give an about the Quantum Machine Learning….
What is Classical Machine Learning and How does it work? -
Humans are always learning from their past experience and machines tend to obey human commands but what would happen if humans could train machines to learn from their past experience and perform tasks with much higher computational advantage? That’s where 'Machine Learning' comes into picture where models are trained based on a particular dataset and then used to make predictions.
Machine Learning can be classified into 2 types:
- Supervised Learning:
Supervised learning uses labelled data to train the model and establish a relationship between input and output then it can be used to make predictions.for example a dataset containing images of people’s facial gestures labelled with their respective emotions can be used as ‘Emotion Detection System’.
In order to establish this relationship between dependant and independent variables, different Models of regression like Decision Trees, Linear regression, Artificial Neural Network(ANN), etc. and classification models like Support Vector Machines(SVM), etc. are used.
- Unsupervised Learning
This type of learning utilizes pattern recognition to make predictions. data used here is non-labelled(unlike supervised learning) and models like clustering and Principal Component Analysis (PCA) etc. This can be used in Fraud Detection Systems.
What is Quantum Machine Learning (QML)? -
Quantum Machine Learning is the extension of the concept of classical machine learning and in QML, large amounts of intensive calculations are performed using high computational advantage of Quantum Computers and it helps to solve many complex problems which are otherwise difficult to solve.
Why do we need QML? -
Classical machine learning involves using feature maps of higher dimensions to analyse and classify data of complicated systems but as system complexity increases, it makes calculations difficult for regular classical computers thus we need QML which utilizes Quantum Computers to solve the issue. #Quantum30
