What is deep learning?
an introduction to deep learning
hey guys, I am quite sure that you have heard deep learning as it becoming a trending technology in the field of computer science today it has many applications around us and I am sure you want to know more about deep learning so you have come to the right place today in this article I would be making you familiar with deep learning
So let’s start
what is deep learning
Deep Learning, is just a type of Machine Learning, inspired by the structure of a human brain. Deep learning algorithms attempt to draw similar conclusions as humans would by continually analyzing data with a given logical structure. To achieve this, deep learning uses a multi-layered structure of algorithms called neural networks.
what are neural networks
A neural network is a series of algorithms that endeavors to recognize underlying relationships in a set of data through a process that mimics the way the human brain operates. neural networks refer to systems of neurons.
to know more about neural networks you can click on the link
Types of neural networks in deep learning
- ANN
- CNN
- RNN
Differences between them
ANN
Artificial neural networks (ANN), usually simply called neural networks, are computing systems inspired by the biological neural networks that constitute animal brains. An ANN is based on a collection of connected units or nodes called artificial neurons
CNN
A convolutional neural network (CNN, or ConvNet) is another class of deep neural networks. CNNs are most commonly employed in computer vision. Given a series of images or videos from the real world, with the utilisation of CNN, the AI system learns to automatically extract the features of these inputs to complete a specific task
RNN
A recurrent neural network (RNN) is another class of artificial neural networks that use sequential data feeding. RNNs have been developed to address the time-series problem of sequential input data.
note — as its a big topic I will make an article to explain it further with examples and everything
How deep learning works
Deep Learning uses a Neural Network to imitate animal intelligence. There are three types of layers of neurons in a neural network: the Input Layer, the Hidden Layer(s), and the Output Layer. Connections between neurons are associated with a weight, dictating the importance of the input value
Applications of deep learning
- image recognition
- computer vision
- chatbots
- natural language processing
- virtual assistants
- self-driving cars
- email spam detection and many more
Conclusion
I hope that today you get to know what is deep learning in the further articles I would be writing more articles for you guys and we would also be making more models on them
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