The fields of business intelligence and predictive analytics have been improving vastly as technological advances are made. Various tools are now available for organizations to implement accurate models to ensure future success, as well as report on existing processes. We understand that reporting and visualizations are important to organizations to communicate findings. Therefore, it is part of our mission to ensure the correct information is communicated and can be visually represented.

It is imperative to understand the mathematics and statistics behind each algorithm, as well as how these algorithms can use your organization’s data to provide insights. Out-of-the-box tools are useful, but Posh Informatics has the capabilities of generating algorithms and models used for predictive analytics from scratch using a variety of languages. This is all dependent on the data that is available and how it is acquired and consolidated.

From start to finish, we are able to analyze the data and recommend or implement the right solution for your business needs.

As of now, Posh Informatics has created a bunch of implementations from scratch and has compared each of them to out-of-the-box libraries/tools. Algorithms that were created from scratch include the following:

• Neural Networks
• Deep Learning
• KNN (Regular and Weighted)
• Support Vector Machines
• Naïve-Bayes
• K-Means Clustering
• Fractional Power Filters

With simple alterations to custom implementations, we are able to exceed the accuracy levels of those tools readily available from different organizations. These implementations were primarily used with images; however, these models can easily be manipulated to look at other types of data to discover patterns or classify data with accuracy levels acceptable to you and your team.