Neural Network

You have rich data, but maybe not the resources to analyze and act on it quickly.

Automating processes through your custom database is a great first step toward getting actionable insights… but to get a sharp competitive edge over competitors or looming challenges, you may want to consider using a neural network to identify opportunities in real-time.

What is a Neural Network?

According to MIT, a neural network is “modeled loosely on the human brain,” and is “a means of doing machine learning, in which a computer learns to perform some task by analyzing training examples.”

In more practical terms, neural networks—also referred to as “deep processing”–are made up of algorithms that assess the relationship between data points. The system then uses its own analysis to predict how other similar types of data points may be related.

For example, if you added a flashlight to an online shopping cart, the site may recommend AAA batteries. If the website is using a neural network to analyze previous purchases recorded in its database, the network may have found that a high percentage of customers who purchased that flashlight also ordered batteries, and therefore recommended the same ones to you.

How Neural Networks Work

Computers have long been better and faster than us at solving complex math equations or sorting data, but humans have an edge on the machines when it comes to making connections between different pieces of information. Artificial neural networks (ANN) are the computer version of that process.

Just like with small children learning to speak, ANNs are taught to recognize types of data and categorize it based on relationships. Once a toddler sees a few dogs and learns to associate the name with the animal, she can begin to identify dogs herself when she meets them. That is also true for an ANN that is being trained on image analysis–after its been fed hundreds or maybe thousands of pictures of dogs, it can start recognizing the features that, taken together, make up a photo of a dog.

Benefits of a Neural Network

Neural networks have been implemented by companies worldwide for a variety of purposes, including…

• Predicting future results based on multiple data inputs
• Recommending products related to those in cart or recently purchased
• Forecasting business performance and financial trends
• Analyzing data sets to proactively alert users of new opportunities
• Detecting fraud and identifying suspicious patterns
• Transcribing audio and video into searchable text
• Translating spoken language in real-time
• Detecting spam or abusive content
• Detecting meaningful patterns in images

As you can see, many organizations can (and already do) get a lot out of neural networks. If you’re interested in learning more about how they might work for your company, contact us today.