Cloudwick’s Machine Learning on Amazon SageMaker Platform is a tool used as the link between machine learning developers and those who may wish to explore the possible use-cases of machine learning for their own business. Cloudwick is partnered with Amazon Web Service to provide this service. The primary application of Cloudwick’s machine learning service is to provide a way for those interested in putting machine learning to work in their own business to quickly and efficiently create, train, and test out machine learning models.
The tiered subscription-based service offers many ready-to-go machine learning models from startup, as well as the support to develop and alter machine learning models not initially included. Cloudwick’s machine learning technology has a lot of use-cases in a large number of fields. It’s also integrated with Amazon Athena, Amazon SageMaker, and is conveniently on the Amazon Web Services platform.
The machine learning service can be used to predict how likely it is each given flight is going to be delayed using data such as how complex the air transit system is and the flight data. It can also be used in cases such as figuring out the likelihood that a given customer will default on their credit card debt using information related to the customer’s past bill history, their demographics such as age and gender, as well as the amount owed.
Several other applications of this technology include industries such as the healthcare field where it can be used to remind patients that are likely to forget their medical appointments, the retail industry where it can predict future sales, and even the public sector where it can help predict where traffic congestion will be and general traffic all throughout the day and help local governments plan out future infrastructure changes.
The major appeal of Cloudwork’s Machine Learning platform is its simplicity and ease of use. As the platform was intended to be used by those who may not have a lot of experience with data science it does a lot to keep things simple, including quick visualizations of predictions and results as well as simplifying the process of exploring data on the platform.