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Introduction to Neural Networks AI | Class 9
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Project Cycle Glossary Class 9
Neural Networks(NN)
A Neural Networks is a combination of algorithms to recognize underlying relationships in a set of data which is like a process that mimics the way the human brain operates.
- Neural Networks reflect the behavior of the human brain.
- Allowing computer programs to recognize patterns and solve common problems in the fields of AI, machine learning, and deep learning.
Neural Networks(NN) is also known as Artificial neural networks (ANN),Neural Networks is inspired by human brain.
Neural networks in everyday life
Social media
The people who are in the social media platforms such as facebook and instagram, people connect themselves with other peoples and make friends online in which people upload their photos or selfies shows to other people, we can also see who else are in their photo and show them their profile names automatically when clicked on the image.
Online shopping
We all know, whenever we are shopping for one thing we end up buying a lot and this happens to all of us most of the time so the technology behind this is recommendations and what we search for.
→ Recommendations
Amazon shows you recommendations depending on the behaviour of the individual interests , Amazon makes use of Artificial Neural Networks(ANN)to train its algorithms to learn the pattern and behaviour of its users. that is why amazon have such a good services and make sure to improve their quality.
→ Search
Yor amazon searches are also use neural network and your amazon return a list of the most relevant products related to your search, It uses past patterns and adapts to what is important for the customer in question.
Online Banking
Online banking has become one of the most common use in everyday daily life, neural networks is used , where you write a cheque you write with your own handwriting and then it is converted into text with the help of neural networks.
Voice-to-text
The voice to text is now a days is very helpful and it is one of the common features on smartphones, in this Technology there is a hand of neural networks.
Smart Personal Assistant
It is one of more common features of voice to text technology , this technology made this new invention of smart personal assistant which is similar as real life personal assistant. for example: Siri,alexa and google are some of the example of smart personal assistants .
Applications of neural networks
Some of the applications of neural networks are :
- Speech recognition
- Character recognition
- Spell checking
Speech recognition
Speech recognition has many applications such as virtual assistance , hands-free computing and video games ,etc neural networks is used widely in this areas .
Character recognition
In this Application of AI is also a use of neural networks in character recognition, where this technology is used to recognize a character with the help of this application of AI.
Spell Checking
Personalized Spell Checking using Neural Networks a new system for detecting misspelled words was proposed. this system corrects the mistakes made by typist.
How Neural Network(NN) works?
The above featured image represents that how Neural Networks work .
In the above image as we can see that the Neural Networks is divided into 3 components.
| Input layer | In this layer, we insert data. |
| Multiple hidden layer | Invisible layer which processes all the input data. |
| Output layer | Gives output of data that was inserted. |
- In the first layer of Neural Networks , there is input data in which we inserts data.
- In the second layer of Neural Networks , there is multiple hidden layers are there which are not visible but all processing occurs in these layers.
- In the third layer of Neural Networks , there is output data which gives the output of data which was processed in the hidden layers.
How Neural Networks(NN) learn
There are three ways neural networks work.
- Supervised Learning is where a computer algorithm is trained on input data that has been labeled for a particular output .
- Unsupervised Learning is in which a system learn through data-sets created by its own. In unsupervised is not labeled.
- Reinforcement Learning Learning through feed-back or trial and error method is called Reinforcement learning.
Features of Neural Networks(NN)
These are some common features of neural networks.
- Neural Networks(NN) system are modelled on the functioning of human brain.
- They are able to automatically extract features without input from the programmer.
- Every neural network is essentially a machine learning algorithm.
- It is useful when solving problems for which the data set is very large.
Neural networks vs Human Nervous system
- As we know that computers have a complex structure and they also can complete any complex tasks in a short time.
- Humans cant do any complex tasks like computers or AI .
- Computers are very fast and intelligent than humans but there are some easy tasks that computers cannot do it. Example: computers cannot babysit a child.
As we know that our brain have billions of interconnected neurons . The interconnections are highly complex. The neurons working in parallel exchanging information through their connectors ‘synapses’, there are Billions of connections among billions of neurons.
History of Neural Networks(NN)
The first step towards neural networks took place in 1943 ,Neural Network was introduced by Warren McCullough and Walter Pitts in 1944 at the university of Chicago.
Warren McCullough was a Brain researcher,neurophysiologist who was one of the discover and researcher of neural networks with collaboration with walter pitt who worked as a logician in the field of computational neuroscience.
For questions of neural networks click here to go through neural networks QA