Better & Faster Predictions With AI
Machine Learning Consulting

As your company grows, analyzing and acting on the massive amounts of data that you’re collecting will become more of a challenge. The more data you have, the more difficult and time-consuming it will become to pull relevant information that can be used to identify patterns and make accurate predictions. Fortunately, AI (artificial intelligence) and machine learning can help to address these challenges.

At Cyber Group, our machine learning consulting team can help you implement AI, machine learning, and deep learning capabilities, all of which can help you identify hidden patterns in customer behavior, predict future behaviors that allow you to make better business decisions, and automate time-consuming tasks thereby allowing you to allocate your valuable resources more efficiently.

Our Sophisticated
Data Strategy

The success of your business depends greatly on your ability to leverage your own data so that you can obtain actionable insights and make better business decisions. It’s why we tailor our data strategy to meet the specific needs and challenges of each client that we work with. The three types of solutions that we will implement as part of your data strategy include:

Predictive analysis is a process in which existing data is analyzed to identify patterns and behaviors. For example, lead scoring is a form of predictive analysis that marketers often depend on to determine whether a lead can be designated as sales ready based on their past behavior.

Lead scoring works like this: a specified number of points is given to each lead based on what actions they take. Once they reach a predetermined score, they are labeled as either a MQL (marketing qualified lead) or a SQL (sales qualified lead). By doing this, you’re essentially predicting whether that lead is likely to be interested in making a purchase or is ready to make a purchase, thereby allowing you to make a more informed decision about how to engage with them.

Predictive analysis can be used in many other ways as well. For example, predicting what types of products customers may be interested in based on what they’ve purchased in the past, when they’ve made prior purchases, and what they have looked at recently. Such predictive analysis can help you to not only close sales at the right time, but also to identify potential up-selling or cross-selling opportunities.

Machine learning allows for similar capabilities as predictive analysis (the ability to make decisions based on predictions). However, there’s one major difference: machine learning is a methodology used to develop algorithms and models that can use cognitive learning techniques to make predictions without having to be explicitly programmed to do so. Our team of consultants have a vast amount of experience implementing a variety of machine learning solutions. The following are some of the areas of machine learning that we are familiar with:

 

TensorFlow

TensorFlow is an open-source machine learning framework created by Google. Essentially, TensorFlow allows for large-scale machine learning by bundling together a number of machine learning and deep learning models and algorithms. By using TensorFlow, you’ll be able to run machine learning models that can perform image recognition, natural language processing, handwritten digit classifications, recurrent neural networks, and more. TensorFlow can seem incredibly complex to those who do not have any programming know-how (specifically, the Python language that TensorFlow uses). Our team is very familiar with Python and has both the experience and expertise required to get the most out of TensorFlow.

 

Artificial Neural Networks

Artificial Neural Networks are a form of machine learning in which a model collects data about a specific process and then uses that data to learn about the process and to understand it. The model can then predict how that process will perform in the future. It’s referred to as an artificial neural network because it was modeled to function like a brain neuron. When a brain neuron receives an input, it will release an output that’s based on that input. This output is then used by another neuron.

LinkedIn is a good example of how an artificial neural network can be used. They use neural networks to identify spam and abusive content on its feeds so that they can remove it. They also use artificial neural networks to better understand what kind of content users are sharing on LinkedIn, which allows them to provide better recommendations to their users.

 

Machine Learning Algorithms

There are three main types of machine learning algorithms that we can implement in your data strategy. These include supervised learning (in which the algorithm is trained using a full set of labeled data), unsupervised learning (in which the algorithm is provided with a dataset without explicit instructions and must analyze its structure to identify useful information), and reinforcement learning (in which the model is trained to make specific decisions based on trial and error).

There are many ways in which all three types of machine learning algorithms can be useful to your business. For example, supervised learning algorithms can help you identify customers who are more likely to churn, unsupervised learning can help you identify potentially fraudulent purchases, and reinforcement learning algorithms can help optimize the space management in your warehouse by learning how to reduce transit time for stocking and retrieving products.

Machine learning is an application of AI and one that is commonly used throughout the business world. However, more advanced AI technology is being applied in data strategies as well. Our consultants have experience working with a number of AI applications for businesses, including the following:

 

IoT ( Internet of Things)

The IoT landscape has expanded significantly over the last decade, to the point where it’s normal to find various IoT devices in households around the country. AI is being used in many of these devices. For example, smart home devices, such as smart thermostats, are becoming a more common application of AI and IoT. These devices provide a lot of valuable data into how they are being used by your customers that can be leveraged to improve your products and services. They should not be ignored when it comes to building your data strategy.

 

Big Data

Big data refers to all of the data that is available to you in digital form, from the data you collect on your website and on social media to the data collected on mobile devices and through your IoT devices. AI applications are necessary to collect, store, analyze, and make predictions using big data — especially as data sources continue to increase and data sets continue to expand. AI technology such as machine learning, automated learning and scheduling, natural language processing, and computer vision will all have significant impact in the future on your big data.

 

Deep Learning

Deep learning is a form of machine learning; however, whereas machine learning requires some guidance (adjustments have to be made if inaccurate predictions are made by machine learning algorithms), deep learning models can actually calculate on their own whether the predictions they have made are accurate or not. It does this by using an artificial neural network to continually analyze data to keep learning. Since it is constantly learning, it can begin to learn unsupervised from unstructured and/or unlabeled data. For example, some chatbots use deep learning to learn how to interact with customers more effectively. Virtual assistants, such as Alexa, also use deep learning to create natural voice experiences.

We Provide Data Integration and
Cloud Deployment

There are many methods and techniques that you can employ to automate tasks and predict customer behaviors, both of which enable you to make more effective and efficient business decisions. In addition to our machine learning consulting services, we can also provide data integration to combine your data from various sources into a single unified view. Our team can also enable SaaS, PaaS, and IaaS solutions via the cloud to help boost your data strategy in a variety of ways (such as reducing the cost of your data strategy and improving the security of your data).

We Help Your Business Advance
In An AI-Driven Enterprise

The success and growth of your business is going to rely significantly on your ability to make effective business decisions. Using machine learning solutions will allow you to identify patterns and predict customer behaviors. Let our consultants at Cyber Group help you implement machine learning solutions, predictive analysis, and AI technologies into a comprehensive data strategy tailored to the needs of your organization.

Boost your business productivity with cutting edge machine
learning. Contact us today.