Join Minitab for an illuminating webinar that delves deep into the statistical foundations of machine learning and showcases real-world case studies in predictive analytics. Explore the intricate world of data-driven insights and decision-making excellence through a statistical lens.
Throughout this session, Minitab will unravel the statistical essence of predictive analytics algorithms, emphasizing their practical applications and significance in the realm of machine learning. Witness how these algorithms leverage statistical principles to transform complex data into actionable predictions, enabling you to anticipate trends and make informed decisions.
Engage with captivating case studies and demonstrations featuring sample datasets that demonstrate the transformative power of statistical machine learning for example how statistical analysis can be used to predict solar energy output and prevent maintenance in industrial machinery. Gain a firsthand understanding of how statistical techniques drive the predictive capabilities of machine learning algorithms.
Additionally, we will highlight the seamless integration of statistical methodologies within the predictive analytics workflow, emphasizing the critical role of statistical thinking in maximizing analytical capabilities and unlocking the true potential of data. Register now to redefine research and development through statistical insights and perspectives.
Presenter: Ming Dong
Job Title: Team Lead, Solutions Architect, Minitab Pty Ltd
Ming Dong is one of only a handful of practitioners across the Asia Pacific Region to be a certified trainer for Minitab’s flagship product, Minitab Statistical Software. The training certification process is the culmination of years of statistical training with real-life application of data analysis in the industry.
Ming’s formal qualifications include an undergraduate degree in Industrial Engineering Management, a Masters of Computer Science from the University of New South Wales, and a Masters of Applied Statistics from Macquarie University. Ming has a unique and profound understanding of the application of statistics in the business world.
In addition, Ming has broad business development experience, developed through his work in senior technical roles for large organisations such as Toshiba, OzEmail and National Computing Systems Singapore. As a university research officer at Macquarie University, he had several papers published in the field of Bioinformatics.
His extensive business development and industry experience are the reason why Ming has been engaged by some of the world’s largest mining, banking and medical devices companies, to provide consulting services in the application of data analysis.
@StatSocAus
