To comprehend the meaning of a neural network, it helps to know first what machine learning entails. Machine learning encompasses a form of artificial intelligence (AI) whereby data is not only collected but also utilized in understanding the behavior of a particular process as well as forecast how that process would act in future settings, as it is fed continuously with new data. Alternatively, a neural network is a type of machine learning that is utilized in detecting various patterns in unestructured data including images and transcriptions.
According to Mark Stadtmueller, Lucd’s VP of product strategy, said that in neural networks when data is gathered about a specific process, the model that is utilized in learning about and comprehending that process and predicting how it will perform in years to come best displays how a brain neuron operates. He added that a brain neuron accepts an input and, in turn, triggers an output that is utilized by another neuron. Additionally, the neuron network mimics the similar behavior in learning about gathered data and then forecasting outcomes.
Deep Learning vs Neural Networks
According to Stadmueller, when a neural network has several layers, it is known as deep learning or deep neural network. He stressed his point by saying that the difference between deep learning and a neural network is that deep learning entails the act of utilizing a subset of neural networks referred to as deep neural networks.
There are several cases in which deep learning is a more suitable approach compared to the use of neural networks only. For instance, when datasets become considerably large, deep learning is beneficial since it can process additional information and complex information accurately and quickly.
According to Anna Knezevic, M&A Solutions’ managing director of financial advisory, said that in various scenarios, deep neural networks are ideal for example with financial applications. She also asserted that the firm’s research and experience have it that utilizing neural networks instead of deep learning builds a superior performance, especially when forecasting financial series such as yield curves.
Many enterprise applications depend mainly on neural networks to come up with solutions for the complex issues. Nir Bar-Lev, the CEO and co-founder of Allegro. Ai, a deep learning platform provider, said that thanks to the neural network’s ability to rapidly categorize and identify volumes of information, almost each tech titan such as Amazon, Microsoft and Google are investing considerably in solving various business issues.
How are Firms Utilizing Neural Networks?
Currently, companies are utilizing neural networks in several ways, depending on their respective business model. For instance, LinkedIn utilizes neural networks together with linear text classifiers to identify abusive or spam content in its feeds once it is created. This information was revealed by the company’s VP of artificial intelligence, Deepak Agarwal.
Tim Hoolihan, DialogTech’s senior director of Data Science and Analytics, asserted that the call analytics startup leverages neural networks in classifying inbound class, especially into predetermined groups or in assigning a lead quality score to calls. According to him, the neural network carries out these functions based on the marketing channel and call transcriptions behind the call.