Neural Networks
Software You Can
Use in Your Business

Neural networks software is a type of algorithm modeled after a the human brain. That’s not to say, however, that neural networks are capable of thinking, creating, and communicating independently in the same way that humans can. 

Instead, a neural network is modeled and designed to work in the same way that a human brain works by sending signals to multiple parts and working together to accomplish a task. 

Neural networks have many applications in the modern business world. For example, there is an artificial neural network software for Excel to help employees maximize their efficiency and accuracy. 

Rossum uses a deep learning neural network that teaches itself how to capture data accurately by mimicking the way a person collects information. 

There are several different types of neural networks. The different types of neural networks use unique techniques and principles that separate them from each other. 

Each type of neural network has its strengths and weaknesses. Some neural networks are used much more than others in artificial intelligence and deep learning applications. 

Here are two of the top neural network algorithms in use today:

• Feedforward Neural Network
  • The Feedforward Neural Network is also called an Artificial Neuron. In a Feedforward Neural Network, the data travels in one direction. The data passes through input nodes and exits on output nodes. 
  • This type of neural network may have hidden layers, but it could also be a single layer or only have visible layers. 
  • Feedforward neural networks are used in computer vision and speech recognition. They are responsive to data with a lot of noise and are relatively easy to maintain. 
• Kohonen Self-Organizing Neural Network
  • A Kohonen Self-Organizing Neural Network uses a Kohonen map to organize vectors that have no relationship to each other into an organized map made of neurons. 
  • The algorithm weighs and analyzes the neurons and finds a classification, and then sorts like vectors to that spot in the map. It places vectors in different parts of the map. One of the Kohonen Neural Network’s strengths is recognizing patterns in data and sorting them. 

What are the uses of neural networks in software?

There are many uses of neural networks in software. For example, Rossum is built on a deep learning neural network. Some of the top companies in the world use neural networks to improve their software offerings, such as Netflix. 

Netflix’s next-level recommendation algorithm is a neural network that can predict and recommend shows to specific users based on their previous views or likes. 

Neural networks have applications within the financial and stock industry where they can be used for financial forecasting. Neural network trading software is meant to increase efficiency and provide the most trustworthy and precise information. 

Neural networks have the capability to analyze and sort data at a capacity that far outweighs normal human ability. So while a neural network may not have the opportunity to predict an accurate financial future based on numbers alone, it can give its users ideas how to manage their funds based on the data it’s been given. 

Neural networks are also used in social media management to discover actionable insight based on how users interact with social media. The information is then used in advertising to show users the correct type of ads based on their activity, preferences, and spending habits. 

Facial recognition software is also a type of neural network growing in popularity in some jurisdictions. Facial recognition software matches recorded human faces to a database of digital images. The neural network can recognize patterns in a human face and match them to an image held in the database, if there is such a match.

Neural networks can be difficult to build, which is why some developers build neural network simulators as tests to see if their models and algorithms work properly. 

Using neural network simulators can also help to strengthen neural networks overall. A “playground” environment makes it easy for neural designers or data scientists to test what does and does not work in a neural network. 

How can you design a neural network?

Developers wondering how to design a neural network may likely turn to Neural Designer. Neural Designer has been described as a software tool that specializes in neural networks and advanced analytics. The software includes tools to create descriptive, diagnostic, predictive, and prescriptive algorithms. 

Neural Designer is viewed as a premier software offering for neural networks. However, it is not free to use. They offer several different payment plans, such as Standard Licenses, AWS Pay as You Go, Academic licenses, and Training programs. There’s even a discounted price for a Neural Designer tutorial. They also offer a free trial. 

The Neural Designer price for a small regular plan is $2,495 per year per user (at the time of this writing). However, they have a scaling price for other sizes and different kinds of options for academic and training purposes. 

A Neural Designer may not be a fit for every business. Developers searching for a neural network designer online can find other kinds of neural network designers that are a better fit for their business’s needs. 

Organizations looking for Neural Designer alternatives can find lists available online at software partners such as G2. 

G2 recognized the top 10 Neural Designer alternatives as 

• RapidMiner
• QlikSense
• Adobe Analytics
• MATLAB
• Posit
• Tableau Server
• SAP Analytics Cloud
• IBM Cognos Analytics with Watson

While some people may want to get around paying for ND or a competitor by discovering a Neural Designer crack, it’s always recommended to license software legally to protect yourself and a possible business against the penalties of the law. 

The Neural Designer blog also offers plenty of insights for Neural Designer users and interested neural network enthusiasts alike. 

A Neural Designer download works both on an offline PC or in the cloud. It’s a powerful neural network simulator that helps developers build, train, and deploy neural network models. Neural Designer is also compatible with Amazon Web Services (AWS).

What is a neural network program?

Instead of downloading a Neural Designer crack, searching for a neural network software open-source alternative is an option. 

An open-source framework is source code that has been made available for free and is able to be modified and redistributed. There are open-source neural network programs available online that enable developers to create and use neural networks.

Here are some of the top open-source neural network programs:

1. Tensorflow
   1. Tensorflow is an open-source software by Google that can be used to build and use neural networks. It is one of the most popular deep-learning frameworks. It is also reported to be very beginner friendly. 
   2. However, there are a wide variety of tools and features that may appear inaccessible to advanced developers used to create their own systems.
2. RNN
   1. RNN (Recurrent Neural Network) is a framework for supervised learning frameworks. It can also be used to design algorithms for deep learning, which are utilized to sort data. 
   2. RNN is one of the more popular frameworks for neural processing and natural language processing. However, some experts feel that it’s not the right choice for machine learning coding due to extra steps of abstraction. 
3. Theano
   1. Theano is a python library for deep learning and is also used in the neural processing and data science communities. 
   2. It can be used to build and train AI models on GPUs and is used by Facebook for training and using AI applications. Theano is compatible with many other neural frameworks. 

Machine learning and neural networks can even be created in software like Excel. A machine learning add-in for Excel allows users to create learning models without programming. 

The learning model can be used to predict changes in the values of data. There are even Excel programs that can be used to create neural network trading software.

What is the best neural network software? 

While there are a lot of free neural network software downloads available online, not every software is a fit for every purpose. If you need a neural network trading software, you might not need the same kind of network as someone working on natural language processing and translation. 

The best neural network software is going to depend on what it is built to do vs. what it is being used to do. 

For example, Rossum uses advanced OCR (Optical Character Recognition) that is built with deep learning neural networks to identify patterns and translate data from a paper sheet to a digital form. It is 98% accurate compared to other models’ 96% or less accuracy. 

Rossum OCR is also six times faster than manual data capture due to the power of its neural network. However, different companies are going to have different needs and uses for neural networks. 

Some of the most highly regarded neural network software are: 

• Neural Designer
  • As previously discussed, Neural Designer is considered one of the very best neural network softwares available on the market today. 
  • Neural Designer is one of the most used software for data mining and can create models for detecting invisible patterns and complicated relationships, as well as for predicting trends.
• Neuroph
  • Neuroph is an open-source neural network software used for creating neural networks and machine learning models. 
• Darknet
  • Darknet is another open-source neural network software. It has nineteen layers, making it capable of very deep computation. It is a pre-trained network and can be used to classify images into thousands of object categories. 
• Keras
  • Keras is a deep learning library used by Theano and Tensorflow. Theano and Tensorflow are both open-source neural network software. 
  • Keras is an API that makes it easier to reduce the cognitive load on people using the software tools. It minimizes the number of user actions necessary for common use cases.