The financial sector (as well as many other sectors) have been quick to embrace the power and usage of machine learning. However anything worth having, takes time to develop. One of the major bottle necks to model development is the feature engineering step and initial test analysis. Taking as much as 40% of the entire workflow.
In this webinar Sr. Data Scientist, Brian Neely, and Director of Artificial Intelligence, Rob Ortiz, will discuss how Ki’s unique capability to perform Automatic Feature Engineering can drastically reduce that time to build a model and help reduce costs and time to deployment.
What you'll learn:
- The challenges faced in custom model creation and the time tables to development
- Why the Feature Engineering step is so critical to good model development
- How Ki uses a wide range of ML/AI based tools to automate these processes.
Meet the presenter: Rob Ortiz
Having joined Keyence in 2004 Rob has had the opportunity to work hand in hand with the largest and most recognized companies in the data age. He is a firm believer in the principle of data guided business decision making and has assisted hundreds of individuals to employ data decision making principles. He believes that effective usage of data is critical to continued growth but must be taken both pragmatically and ethically.