- Amazon Web Services
Not so long ago, machine learning (ML) algorithms were used only by research scholars with few industrial use cases. ML algorithms did not have their own place in our daily lives.
Gone are those days: in today’s modern world, not a single day passes without having an interaction with the results of an ML algorithm – be it from the way the search results are ordered by your search engine to the ways you interact with your smartphone, to the ways you get introduced to new music and TV shows – its presence is ubiquitous. ML algorithms have not just found their place but they are influencing our lives on a day-to-day basis. So how can you start to solve business problems by effectively leveraging ML algorithms?
Amazon Web Services (AWS) has been a consistent leader in the cloud infrastructure market and offers a staggering number of services catering to data storage, data processing, and analytical capabilities, including machine learning. If you are eager about learning how to build scalable ML models using AWS, this webcast is for you.
Advanced Analytics in Amazon Web Services (31 minutes)
In this webcast we:
- Touch upon the wide spectrum of analytic opportunities ML can be applied to
- Introduce AWS and Amazon SageMaker, a fully managed service to deploy ML models quickly
- Discuss the various features of Amazon SageMaker
- Demonstrate building an ML model using Amazon SageMaker
Is it for you?
- Do you want to quickly derive business-focused insights to keep up with the unprecedented circumstances?
- Has your primary investment been on-premises, and now you’re looking to migrate to the cloud?
- Are you looking to enhance your current applications by leveraging AWS?