{"id":26114,"date":"2020-11-24T08:49:06","date_gmt":"2020-11-24T16:49:06","guid":{"rendered":"https:\/\/careerkarma.com\/blog\/?p=26114"},"modified":"2020-11-24T08:49:09","modified_gmt":"2020-11-24T16:49:09","slug":"neural-networks","status":"publish","type":"post","link":"https:\/\/careerkarma.com\/blog\/neural-networks\/","title":{"rendered":"Learn Neural Networks: Best Courses to Build Learning Pathways for Machines"},"content":{"rendered":"\n

If you are interested in creating learning algorithms<\/a> that can inform modern artificial intelligence, studying neural networks will put you on the cutting edge of these developments. Consider taking a machine learning<\/a>, deep learning<\/a>, or neural network course to get into the exciting field of artificial intelligence<\/a>.
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Read on to uncover more about neural networks and their modern applications. We will also discuss how a neural network works, how to learn it step-by-step, and the best courses for in-person and online study.<\/p>\n\n\n\n

What Is a Neural Network?<\/h2>\n\n\n\n

An artificial neural network functions in much the same way as the neural network in an animal or human brain. It is a collection of connected nodes that make up artificial neurons. The first layer of nodes holds a number that corresponds to a pixel in an image. The last layer predicts what the machine believes the original image might be.
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This trial and error process begins with the input layer that you want the machine to learn and ends with what the machine \u201cthinks\u201d is the correct answer in the output layer. Neural networks are a valuable tool for neuroscientific research, machine learning algorithms, and computer science.
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There are two main types of neural networks. Convolutional neural networks, or CNN, are used for photo tagging, and recurrent neural networks, or RNN, are used in speech recognition or machine language translations.<\/p>\n\n\n\n

Neural Network Applications<\/h3>\n\n\n\n

So, what are neural networks used for? They are used to allow a machine to learn from many data sources in ways that humans can\u2019t. Below are just some of the applications of neural networks today.<\/p>\n\n\n\n

Restoring Image Colors<\/h4>\n\n\n\n

Instead of hiring a colorist to spend months restoring a photo or a black and white video, neural networks can do it instantly. The neural network can recognize color patterns in our world, like the blue sky and white clouds. The more information the network retains, the better its images become.<\/p>\n\n\n\n

Generating Music <\/h4>\n\n\n\n

Sony used neural networks to generate a recording of \u201cOde to Joy\u201d as it was originally intended, as well as a Brazillian guitar version. The idea of machines making music seems more like AI than deep learning, but it is neural networks that teach the machine the notes and sequences.<\/p>\n\n\n\n

Helping Endangered Species<\/h4>\n\n\n\n

A neural network was created to identify endangered whales via images, which can be applied to machine learning to help save the endangered species. <\/p>\n\n\n\n

Reading Human Handwriting<\/h4>\n\n\n\n

In this case, the input is a handwritten letter or number, which the neural network will learn from to be able to predict what the image says. Although this requires a lot of trial and error, it is incredible that a computer can be trained to read variations of human handwriting. <\/p>\n\n\n\n

Replicating Human Speech<\/h4>\n\n\n\n

Human speech is arguably the most spine-chilling application of a neural network. Much like a child learning to talk, a machine can learn to form words and sentences, starting with gibberish at first, and slowly improving using natural language processing.
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Recognizing Faces<\/p>\n\n\n\n

As you may know, the tags used on Facebook photos are created using neural networks. These neural networks are also being used to reconstruct pixelated images into a recognizable form, which has massive potential for solving crimes.<\/p>\n\n\n\n

Translating Languages<\/h4>\n\n\n\n

Google Translate now has an algorithm that can translate a word or phrase into another language based only on a photo of the word.<\/p>\n\n\n\n

Developing Self-Driving Cars<\/h4>\n\n\n\n

Self-driving cars are one of the most well-known applications of machine learning. In the future, we might all be able to sit back, relax, and watch the world go by as our cars take us where we need to go.<\/p>\n\n\n\n

How Neural Networks Function<\/h3>\n\n\n\n

Below is an example of a straightforward neural network and how it can be used to decipher different dog breeds based on photos.
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