Artificial Neural Network backpropagation intuition

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Artificial Neural Networks (ANN) have emerged in the past few years as an area of unusual opportunity for research, development and application to a variety of real world problems. Examples include handwritten digit recognition, language translation, scene understanding to list a few which are complex systems to program and model mathematically.

An Artificial Neural Network is a computational model based on the structure and functions of biological neural networks. Information that flows through the network affects the structure of the ANN because a neural network changes – or learns, in a sense – based on that input and output (source https://www.techopedia.com).

In this blog post our partner GuRu Prevails talks about ANN inner mechanics of forward propagation, backward propagation and mathematical intuition behind it. GuRu Prevails is India’s first and finest organization in the fields of Machine Learning and Consulting Services. GuRu Prevails has wide experience in coaching professionals on how to connect the dots of business cases with mathematics and computations. Customers of GuRu Prevails include IBM Watson Labs, SAP Labs, Startups in India and some of Indias top Universities.

To read the blog post, please download the PDF file here.

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