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Here are some key points about deep learning:
• The structure of deep learning models is inspired by the neurons and connections in the human brain.
• Artificial Neural Networks (ANNs), or Neural networks, are the core of machine learning.
• These networks consist of node layers, including an input layer, one or more hidden layers, and an output layer.
• If the output of any node exceeds a certain threshold, the node is activated, sending data to the next layer. Otherwise,
no data is passed along.
• When the network has more than three layers, including the input and output layers, it is called a Deep Neural
Network (DNN).
Multiple hidden layers
Input layer
Output layer
Difference in
desired values
Backprop output layer
Brainy Fact
In 2016, Google’s AlphaGo beat Go master Lee Sedol utilising deep learning neural networks most closely
approaching human thought.
Applications of Deep Learning
Here are a few examples of deep learning at work:
• Automated Driving: Deep learning is used to spot stoplights and traffic signals and also to detect pedestrians,
reducing the incidence of accidents.
• Aerospace and Defence: Identifying objects from satellites and locate safe and unsafe zones for troops is another
area where deep learning is playing a major role.
• Medical Research: Cancer researchers use deep learning to automatically detect cancer cells.
• Industrial Automation: Deep learning helps detect when people or objects are within an unsafe distance from the
heavy machines thereby ensuring their safety.
Machine Learning
Machine learning refers to the field of artificial intelligence where computers are trained to learn from data and make
decisions or predictions. It encompasses supervised learning (using labelled data), unsupervised learning (finding
patterns in unlabelled data), and reinforcement learning (learning through trial and error).
Machine learning is widely applied in areas such as image recognition, natural language processing, and autonomous
vehicles to automate tasks and enhance decision-making processes.
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