Presented by the IEEE Consultants Network of Florida's West Coast.
Machine learning is driving innovation in many application areas, including movie recommendations, fraud detection, digital health monitoring and advanced driver assistance to name a few. Developing machine learning models and deploying them on embedded systems or cloud infrastructure often still requires significant expertise with signal processing, big data, and model optimization.
This presentation begins with an overview of machine learning, including various types of machine learning, the workflow, and what makes building predictive models challenging. You will learn what the hot topics Deep Learning and Artificial Intelligence are all about relative to Machine Learning.
Then, in the context of real world applications, this talk addresses how MATLAB® empowers engineers and scientists without significant signal processing and machine learning expertise to:
Quickly build initial predictive models without writing any code
Optimize performance, including hyperparameter tuning
Scale processing to big data and cloud computation
Leverage advanced signal and text processing techniques
Deploy models in production IT systems or on embedded devices
We will conclude with key industrial innovations driven by Machine Learning, such as optimizing equipment maintenance and monitoring production systems.
Bernhard Suhm, Machine Learning Product Marketing Manager, MathWorks
Bernhard Suhm is the Product Marketing Manager for machine learning at MathWorks. He works closely with customer facing and development teams to address customer needs and market trends in our machine learning related products, primarily the Statistics and Machine Learning toolbox. Prior to joining MathWorks Bernhard led analyst teams and developed methods applying analytics to optimizing the delivery of customer service in call centers. He also held positions at a usability consulting company and Carnegie Mellon University. He received a PhD in Computer Science specializing in speech user interfaces from Karlsruhe University in Germany.
IEEE membership is not required. All are welcome.
IEEE Member: $15, Non Member: $20, Student: $10
Pizza and non-alcoholic refreshments provided.
Register at: https://events.vtools.ieee.org/m/198874