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What is Deep Learning and How Does it Work?

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At a very basic level, deep learning is a machine learning technique. It teaches a computer to filter inputs through layers to learn how to predict and classify information. Observations can be in the form of images, text, or sound. The inspiration for deep learning is the way that the human brain filters information. Its purpose is to mimic how the human brain works to create some real magic. In the human brain, there are about 100 billion neurons. Each neuron connects to about 100,000 of its neighbors.


What is Deep Learning and How Does it Work?

#artificialintelligence

Sit back, relax, and get comfortable with cool concepts like artificial neural networks, gradient descent, backpropagation, and more. The inspiration for deep learning is the way that the human brain filters information. At a very basic level, Deep Learning is a Machine Learning technique. It teaches a computer to filter inputs through layers to learn how to predict and classify information. Observations can be in the form of images, text, or sound. The inspiration for Deep Learning is the way that the human brain filters information. Its purpose is to mimic how the human brain works to create some real magic.


Introduction to Artificial Neural Networks - KDnuggets

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Deep Learning is the most exciting and powerful branch of Machine Learning. It's a 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. Deep learning is getting lots of attention lately and for good reason. It's achieving results that were not possible before. In deep learning, a computer model learns to perform classification tasks directly from images, text, or sound.


Understanding and coding Neural Networks From Scratch in Python and R

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I prefer Option 2 and take that approach to learning any new topic. I might not be able to tell you the entire math behind an algorithm, but I can tell you the intuition. I can tell you the best scenarios to apply an algorithm based on my experiments and understanding. In my interactions with people, I find that people don't take time to develop this intuition and hence they struggle to apply things in the right manner. In this article, I will discuss the building block of a neural network from scratch and focus more on developing this intuition to apply Neural networks.


Simply deep learning: an effortless introduction – Towards Data Science

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This article is part of the Intro to Deep Learning: Neural Networks for Novices, Newbies, and Neophytes Series. Let's start with a quick recap from part 1 for anyone who hasn't looked at it: At a very basic level, deep learning is a machine learning technique. It teaches a computer to filter inputs through layers to learn how to predict and classify information. Observations can be in the form of images, text, or sound. The inspiration for deep learning is the way that the human brain filters information. Its purpose is to mimic how the human brain works to create some real magic. Deep learning attempts to mimic the activity in layers of neurons in the neocortex.