AI Analytics Through Machine Learning
& TensorFlow Consulting

Using AI technology to improve your data strategy will not only free up valuable time, but also help identify patterns and trends that can be used to forecast future events. This can be done through machine learning techniques. Here at Cyber Group, we not only have a firm grasp on how to implement machine learning to improve your data analytics and forecasting abilities, we can also employ TensorFlow, which is an open-source software library built by Google for the purpose of implementing deep learning systems.

We Help You Modify TensorFlow According To Your Business Needs

Our TensorFlow consulting team has the programming expertise required to work with TensorFlow and to modify it to meet your business needs. Using TensorFlow, we can implement a variety of different machine learning techniques to address many analytics challenges, including image recognition, natural language processing, sentimental analysis, product/service recommendations, and more.

We Help You Modify TensorFlow
According To Your Business Needs

TensorFlow can have a huge impact on your data analytics capabilities. Consider these ways in which you will be able to benefit from our expertise and experience using TensorFlow:

Deep learning is an advanced version of machine learning. Machine learning is a process in which computers are taught how to process and learn from data. With deep learning, the computer is able to train itself to process and learn from that data. Deep learning models require neural networks with more than three layers.

Neural networks are sets of algorithms that are modeled after the human brain’s biological neural networks. They are capable of storing enormous datasets and can learn to perform tasks based on the data that they have access to without being given specific instructions. We can create and build neural networks to help cluster and classify your data based on similarities to example input. A basic neural network has three layers. The first layer is where data enters the system, the second layer (which is hidden) is where the information is processed, and the third layer is where the system decides what to do based on how the information was processed.

Building a complex deep learning model isn’t the only option when using TensorFlow. We can also build linear models, which only use a single weighted sum of features to formulate a prediction. They are much simpler, but there can be an advantage to this depending on what they’re used for. For example, linear models can train much faster than deep neural networks, they don’t require a lot of adjustments when it comes to learning rates, they can be easily interpreted and debugged, and they’re a good starting point.

TensorFlow can be used to build a variety of solutions to help address your unique challenges and meet your specific business needs. Some of the TensorFlow solutions that our team can help design and create include:

 

To Text

Performing sentiment analysis, detect spam, detect intent, label topics, and more, requires text classification, which can be done in TensorFlow. Text classification involves labeling text with tags or categories based on its content. This needs to be done to obtain any kind of insights from unstructured data in the form of text.

 

To Data Analytics

Using TensorFlow, we can build advanced predictive modeling applications to improve your data analytics capabilities. We can build these models using regression, classification, and clustering algorithms.

 

To Images

Analyzing visual data has always been a big challenge. This is because while images are easy for humans to identify, the lack of text or numbers makes it difficult for computers to identify. Building a convolutional neural network using TensorFlow will make it possible to classify images through the use of a spatial-invariance technique that allows it to learn local patterns in images.

 

To Neural Network

Neural networks can be implemented via TensorFlow to perform deep learning analytics. There are many types of neural networks that we can build to meet specific needs, including feed forward neural networks, convolutional neural networks, recurrent neural networks, and more.

Our team provides a lot of flexibility when it comes to TensorFlow because they are proficient in all of the main programming languages that are supported by TensorFlow, including the following:

 

C++

C++ is a general-purpose programming language that’s an extension of the C language. It’s mostly used by programmers or developers for applications and games. C++ was also used to develop the Chrome browser and is used for open source database software as well, which is why it’s supported by TensorFlow.

 

Java

Java is another general-purpose programming language that was created to provide developers the ability to run their applications everywhere while only having to write it once. TensorFlow does provide a Java API, which is helpful if you need to run TensorFlow models within a Java application.

 

Python

Python was the first client language supported by TensorFlow and continues to be the best supported language, which means that it supports the most features.

 

Swift

If you’re working on a Mac or Linux operating system, Swift is a helpful language to know. It’s a general-purpose, multi-paradigm, compiled language developed specifically by Apple.

 

Javascript

JavaScript (not to be confused with Java) is a scripting language that serves as one of the core technologies for the Internet. It’s what enables web pages to be interactive — almost all websites use JavaScript.

 

Ruby

Ruby is an interpreted, high-level, general-purpose language that supports object-oriented, procedural, and functional programming. Many developers use the Rails framework, which is written in Ruby, to build their websites and applications.

Gain Meaningful Insights On
Projections And Forecasts

The deep learning capabilities of TensorFlow’s open-source software library will allow you to dive deep into your data to not only discover hidden patterns and trends but to identify relationships within your data that can be used to make more accurate forecasts and projections. If you know how to use and leverage TensorFlow effectively, you’ll benefit from meaningful insights that could not only improve your decision making, but also increase efficiency across your organization.

Outsource Your TensorFlow Projects to the Experts

TensorFlow can be incredibly beneficial to your data strategy for machine learning and data analytics. However, it can also be a bit overwhelming, especially if you’re not familiar with programming languages. Relying on our TensorFlow consulting services will enable you to take advantage of machine learning techniques to obtain more actionable insights and more accurate predictions than ever before.

Start implementing TensorFlow and improve your business
procedures by contacting us today.