Many research scientists and tech enthusiasts have wondered for years if machines could learn or be trained to think like humans.

In 1959 while at IBM Arthur Samuel, an American pioneer in the field of computer gaming and artificial intelligence, coined the term “Machine Learning.” Decades later, we finally implemented modern scenarios using Machine Learning.

The field of Machine Learning (ML), explores the study and construction of algorithms that can learn and make predictions based on data. To put it in simpler terms, you take a few input samples (data), build a model, choose an algorithm to understand the data better, train the machine to learn and establish baseline behavioral profiles for various entities and then use it to find meaningful anomalies.

Imagine when you were young, you were taught to identify “things.” For example, as a child, we learned how to identify automobiles. After observing several different types of vehicles, your brain began to learn how to register an image of a vehicle; then your brain began to learn how to differentiate between cars, trucks, and motorcycles. The more images your brain captured, the more accurate you become in identifying vehicles. The same is true for ML. To implement ML, we need data, lots of data. The more data you have, the better the machine learning experience will be.

At BizCloud Experts, we used a publicly available CRM (Customer Relationship Management) data set to train our prediction model using Binary Classification to identify customers who Churn. Churn rate is an important consideration in the telephone and cell phone services industry. In many geographical areas, several companies are competing for customers, making it easy for people to transfer from one provider to another. These customers have multiple options to choose from within a given geographic area.  Therefore understanding your customer churn rate helps a telco provider determine how it measures up to its relevant competitors. We used Amazon Machine Learning to train our model, evaluate it and make predictions. We integrated this data model with our Client’s CRM tool to make real-time predictions based on the customer information we found in their CRM database to determine a customer’s potential to churn. Then we made the model interactive by introducing Machine Learning to automate Agent Call Routing depending on the churn status so that a customer at risk was routed directly to customer service agents known for providing a 5-star service experience to increase retention, thus providing a win-win scenario for both the client company as well as the customer. We are actively engaged on implementing the same to logistics, where video analysis would provide us data related to tracking inventory real time, minimize the ground transport interaction to avoid anomalies and aide in Efficient Asset Management.

A human might tend to make mistakes over time when presented with all of this extra information. The opposite is true; a machine would better understand or learn from all of this additional data.

Do you think your organization could benefit from ML? Planning to implement a similar use case for your business? At BizCloud Experts, we are a team of certified solution architects and developers who can help you move your business to the cloud where you can fully utilize the enormous advantages of ML. Contact us for more information about the cloud services we offer by dialing 214-206-8976 or visit us at

If you have any questions please email us at and if you would like to join our meetup please visit the link.

Thank you

BizCloud Experts