Goto

Collaborating Authors

Overview of Artificial Neural Networks and its Applications

#artificialintelligence

The term'Neural' is derived from the human (animal) nervous system's basic functional unit'neuron' or nerve cells which are present in the brain and other parts of the human (animal) body. Dendrite - It receives signals from other neurons. Soma (cell body) - It sums all the incoming signals to generate input. Axon - When the sum reaches a threshold value, neuron fires and the signal travels down the axon to the other neurons. The amount of signal transmitted depend upon the strength (synaptic weights) of the connections.


Overview of Artificial Neural Networks and its Applications

#artificialintelligence

The term'Neural' is derived from the human (animal) nervous system's basic functional unit'neuron' or nerve cells which are present in the brain and other parts of the human (animal) body.


A Beginners Guide to Neural Nets

#artificialintelligence

To give the NN some context we will consider one of the original problems it was applied to - handwritten digit recognition [4]. This problem is often one of the first encountered by students of Deep Learning as it represents a problem that is hard to solve with traditional machine learning methods. Imagine that we are tasked to write a computer program that can identify handwritten digits. Each image we receive will be 28 x 28 pixels and we will also have access to the correct label for that image. The first thing we do is set up our neural network as in the figure below.


An Intuitive Guide To Understanding The Learning Process Of A Neural Network

#artificialintelligence

Artificial neural networks are one of the most widely used methods in machine learning. And one of the most interesting things about a neural network is the way it learns about the data it's been trained on. It first starts by learning simple patterns in the data and then proceeds to learn more complex attributes. I decided to write this article after taking a class on neural networks and reading lots of articles about it. Even though I understood the structure of a neural network, and the process involved in adjusting the weights required to make proper predictions, it wasn't still clear to me why it worked the way it did.


Introduction to Artificial Neural Networks - KDnuggets

#artificialintelligence

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.