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STAGE 1 The design brief Modern technology and new concepts have increased the reliability of machines over humans. We rely on machines to make our

STAGE 1
The design brief
Modern technology and new concepts have increased the reliability of machines over humans. We rely on machines to make our lives safer and easier, whether it is making calculations or scanning our retinas for recognising people's identities. It is a fact that has been proven by the amount of research and development undertaken in the field of Al, particularly deep learning and machine learning.
The amount of research work going on in the field of deep learning and machine learning completes the task of object classification in photographs to adding sound to silent movies. Similarly, handwritten text recognition is one of the significant areas of research and development with a lot of posibilities. Handwriting recognition (HWR), also known as Handwritten Text Recognition (HTR), is the ability of a computer to receive and interpret intelligible handwritten input from sources such as paper documents, photographs, touch-screens and other devices. Handwritten Text recognition is an important application of deep learning and machine learning. This technique is helpful in detecting forgeries while verifying signatures, interpreting , 'ostal addresses, processing bank cheques, etc.
Nearal Networiss "Neural Nelworks"
Likewise, handwritten digit recognition is the ability of a computer to recognise the hul n vn handwritten digits and classify them into ten predefined classes (0-9). This is one of th' famous topics of boundless-research in the field of deep learning. Digit recognition has n any applications like number plate recognition, postal mail sorting. bank check processing. etc. In handwritten digit recognition, many challenges are faced because of different styles of writing.
As a grade 12 student, you must now apply the skills you have learned to design an ANN model to solve a problem.
Imagine you are a trainee Al engineer who needs to build an ANN model to classify handwritten digits in order to be able to use it in ddifferent applications be your task for the next fow veeks. Having done so you should develop a business model for an application of your own choice and prepare to present your idea to possible invesiors.
You will now complete your STREAM project to create an ANN model to recognise handwritten digits for your chosen application (RTA, Bank, Police investigation etc.), using Python programming language.
Activity 2.2.1
In this space below, list and explain at least 4 keywords from the design brief
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