Machine Learning for Business on AWS (2/2)

Machine Learning is fast becoming one of the biggest tools for gaining insights from business data.

In this 2-part series, Taysols will guide you step by step through the process of setting up a machine learning environment on the world’s leading Cloud Platform, AWS, in your business, so you can also start to benefit from AI.  Additionally Janine Xavier, Head of Business Intelligence at GPT will be taking you through how GPT has commenced their Machine Learning journey. This is a great opportunity to hear about the principles underpinning the start of a successful machine learning journey from one of Australia’s leading organisations.

Part 2: How to incorporate a ML model on AWS using a Churn use case

In the previous session we showed how to set up a machine learning model on Amazon SageMaker. However, to take advantage of these models, and for businesses to become data-driven organisations, these need to be architected so that they are autonomous and the data produced is available to business end users. Using a customer churn example we show how to adopt the various AWS services to achieve this as well as giving you insights into how a production machine learning solution should be set up on AWS.

About the speakers:
Janine Xavier has been leading teams in the Business Intelligence and Analytics space for a number of years and brings very strong Finance and Business acumen to her role. This combination of strategic thinking and business understanding has allowed Janine to forge a successful career assisting large organisations achieve excellence with data and analytics and is currently laying the same foundations at GPT, as the head of Business Intelligence.

Daniel Bassett is a PhD qualified data scientist with a passion for answering questions with sophisticated analytical tools and techniques. His unique combination of skills in science and computer programming has allowed him to create specific tools to analyse and solve difficult data-based problems and further lead to the translation of business data and requirements to meaningful and easily understood output. Daniel is Taysols' Chief Data Scientist.

EVENT DETAILS

 PART 1: HOW TO BUILD AND PICK A ML MODEL FOR YOUR DATA
If you are interested in attending also the first part of this series, please click here.