Machine Learning is fast becoming one of the biggest tools for gaining insights from business data. Businesses that adopt machine learning will stand to gain a significant competitive advantage and yet getting started can be a daunting task. In these sessions we aim to take 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.
Now, more than ever, organisations can take advantage of these systems and become data-driven organisations, gaining deep insights from their data, and use these insights to make critical business decisions that will allow them to become a leader in any industry.
The power of machine learning is the ability of the program to self-learn and investigate multiple patterns within the data simultaneously. This process uncovers trends within the data that were previously indiscoverable by traditional methods.
In a nutshell, computers are able to tap into different types of hidden insights without being explicitly programmed to do so. It does not require someone to understand the data first, with machine learning the understanding of the data comes to you. With the scale that AWS provides in both compute and storage as well as their market leading ML solution, Sagemaker, the world's leading cloud platform is perfectly positioned to help you on your journey to deeper insights.
Despite these obvious advantages many businesses don't know where to start, or know what needs to be considered.
In this 2-part series, Taysols' Chief Data Scientist will
Part 1: How to build and pick a ML model for your data.
Machine learning is set to become one of the biggest tools for gaining insights from business data. Businesses that adopt machine learning will stand to gain a significant competitive advantage and yet getting started can be a daunting task. AWS lowers this barrier of entry to adopting machine learning models for business users every day.
In this complimentary 1.5-hour event we show how to use Amazon SageMaker to build a machine learning model within your business and how to choose from the plethora of currently available machine learning models.
About the speaker:
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
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MELBOURNE |
SYDNEY |
Click here to register also for part 2 of this series, running in March 2019: How to incorporate a ML model for your data.