Deep Learning is a subfield of machine learning that is inspired by the structure and function of the human brain, specifically neural networks. It is a key technology behind driverless cars, enabling them to recognize a stop sign or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers.
Understanding Deep Learning
Deep learning is a machine learning technique that teaches computers to do what comes naturally to humans: learn by example. Deep Learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost. It is the key to voice control in consumer devices like phones, tablets, TVs, and hands-free speakers.
Neural Networks
Neural Networks are a series of algorithms that mimic the operations of a human brain to recognize relationships between vast amounts of data. They are used in a variety of applications in financial services, from forecasting and marketing research, to fraud detection and risk assessment.
Role of AI in Deep Learning
AI, or Artificial Intelligence, is the concept that a computer system can be made to perform tasks that would usually require human intelligence. These tasks include learning and problem-solving, which are key aspects of Deep Learning. AI is an integral part of Deep Learning, as it provides the algorithms and neural networks that allow the systems to continually learn and improve.
Deep Learning and Machine Learning
While Machine Learning is a subset of AI, Deep Learning, in turn, is a subset of Machine Learning. Deep learning algorithms are based on artificial neural networks, particularly convolutional neural networks (CNN). Machine learning uses algorithms to parse data, learn from it, and make informed decisions based on what it has learned.
Algorithms and Training in Deep Learning
Algorithms in Deep Learning are based on improving and optimising a function that gives a measure of difference between the network’s output and the actual output. The process of improving and optimising this function is known as Training. Training involves feeding the neural network with data and allowing it to adjust its internal parameters to better predict the desired output.
In conclusion, Deep Learning is a rapidly growing area of AI and Machine Learning that is based on neural networks and algorithms. It offers immense possibilities for the future, from driverless cars to voice control in consumer devices. It is a field that will continue to grow and evolve, and one that offers great potential for businesses and individuals alike.
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