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Benign or Malignant? How AKA Used Azure Automated Machine Learning to Predict a Tumor—Without ANY Coding
Taking data and making it work for your company isn’t always an easy feat. As a Microsoft Dynamics 365 CRM technical consultant at AKA Enterprise Solutions, I’m constantly working with large databases of CRM data and it got me to thinking—what are the best solutions available for putting massive amounts of data to work? After a bit of research, I was introduced to Azure Automated Machine Learning from Microsoft. This solution was especially interesting to me because it was designed to be a no code (or low code) solution, compatible with datasets from an array of sources—including CRM, SQL, Blog storage and so on.
Why Choose Microsoft’s Azure Automated Machine Learning
Azure Automated Machine Learning takes a given dataset and swiftly trains machine learning models to discover relationships in this data. The key to Automated Machine Learning is its ability to see relationships that even experienced humans can’t. This technology enables businesses to gain a deeper understanding of their business as a whole and how clients interact with their company. Automated Machine Learning allows companies to take data and ultimately turn it into a better experience for their customers. This solution from Microsoft can also be deployed as a web service, so it can be used in other applications like Power BI, etc.
In the past machine learning was a new technology—both expensive and time consuming to implement. Microsoft was able to push past these barriers with the Azure Automated Machine Learning application, which is included with Azure. Although the CRM data analysis solution isn’t free, it is reasonably priced for what it delivers. Microsoft even provides users access to their project cost calculator to manage and plan costs before you jump in with both feet.
The time investment from start to finish varies, but I took a raw dataset from Breast Cancer Wisconsin (Diagnostic) and turned it into a fully trained machine learning model that can predict whether a tumor is benign or malignant in just one hour. It’s pretty amazing that this tool could take 569 digitized breast cancer tumor images and deliver their binary classification so quickly!
See just how I used Azure’s Automated Machine Learning Application to classify breast cancers tumors from a dataset in only 21 steps:
These types of results aren’t limited to healthcare—just imagine the possibilities for your industry. If your business wants more from your data, Microsoft’s Azure Automated Machine Learning may be the next step. You can learn more about this CRM data solution by reading Microsoft’s Azure Automated Machine Learning documentation. Or, contact AKA’s Azure experts and we will can help you get started or answer your questions.
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Article by: Nick Castro | 212-502-3900
Nick Castro is an Associate Technical Consultant at AKA Enterprise Solutions. With a strong background in Computer Science, Applied Mathematics and Statistics, and multiple Dynamics 365 certifications, he is able develop innovative and unique CRM solutions.