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Artificial Neural Network:


Deep learning is a subfield of machine learning concerned with algorithm inspired by the structure and function of the brain called "Artificial Neural Network". In a nutshell, below is the function of a neuron. Axon: is a stem for processing output. Perceptron's work in a similar way like Neuron, it takes input and perform transformations and produces the results. Inside the perceptron, we typically calculate the step function.

Single-Layer Neural Networks and Gradient Descent


This article offers a brief glimpse of the history and basic concepts of machine learning. We will take a look at the first algorithmically described neural network and the gradient descent algorithm in context of adaptive linear neurons, which will not only introduce the principles of machine learning but also serve as the basis for modern multilayer neural networks in future articles. Machine learning is one of the hottest and most exciting fields in the modern age of technology. Thanks to machine learning, we enjoy robust email spam filters, convenient text and voice recognition, reliable web search engines, challenging chess players, and, hopefully soon, safe and efficient self-driving cars. Without any doubt, machine learning has become a big and popular field, and sometimes it may be challenging to see the (random) forest for the (decision) trees.

Perceptron: A Basic Neural Network Model for Deep Learning


The World has witnessed an explosion in machine and deep learning technology in the last decade from a personalized world to professional activities everywhere. With these technologies, I am sure that you had heard or read the term "Perceptron" in the neural networks which is the first concept one will probably start to learn neural network. Therefore through this article, my emphasis is to show what is a perceptron and its working. An American Scientist Rosenblatt was very much inspired by the biological neuron and its ability to learn and the term perceptron was introduced by him around 1957. Rosenblatt's perceptron has one or more inputs with only one output and a processor.

20 Minute Machine Learning Crash Course


At the brand new Climate Pledge Arena in Seattle, Amazon debuted their Just Walk Out cashierless technology to enable fans to get out of their store and back in their seats as quickly as possible. This impressive system by Amazon is a recent application of artificial intelligence, one of the most promising emerging technologies that will have (and already is having) a major impact on our world. If you are inspired by this or other applications of AI to utilize the technology in your own way, you have to start somewhere. This guide will help you get started with the technical side of AI, starting from defining what a neural network exactly is to finding ways to optimize training of a neural network. Images in this guide are from this free course on Udacity. Feel free to check it out! Neural networks are tools that can be used to solve classification problems. Given an image of a dish, classify it as a pancake or a waffle. Given a handwritten number, classify it as a digit from 0–9. In the above graph, we are trying to predict whether or not a student gets accepted into a particular university based on their grades and test scores.