On-Demand Webinar

Computer vision using SAS Dlpy


About the webinar

In this Webinar, we will discuss the application of Deep Learning models using Deep Learning Py focusing on Computer Vision.

DLPy is a high-level Python API designed to provide an efficient way to apply Deep Learning functionalities using friendly Keras-like APIs to solve Computer Vision, Natural Language Processing, Forecasting, and Speech Processing problems. We explain how DLPy can be applied to data preparation, data processing, model building, assessment and deployment. 

Finally, we provide a step by step guide on image tagging using multitask learning, which is a subfield of machine learning in which multiple relevant learning tasks are solved at the same time, exploiting commonalities and differences across the different tasks.

During the webinar we'll explore?

  • Give an overview of Computer Vision
  • Discuss some of the challenges in a Computer Vision project and how to overcome them
  • Give examples of real use cases where this has been implemented

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About the Experts

Spiros Potamitis
Data Scientist at SAS

Spiros Potamitis is a data scientist at SAS, specialising in the development and implementation of advanced analytics solutions across different industries. Having acquired an MSc in Computer Engineering and one in Information Management Spiros provides subject matter expertise in the areas of Machine Learning and AI. 

Prior to joining SAS, Spiros has worked and led advanced analytics teams in various sectors such as Credit Risk, Customer Insights and CRM.

Niall Larkin
Data Scientist at SAS

Niall is a new addition to the SAS workforce, recently graduating from the customer advisory programme in Cary, NC. Prior to joining SAS Niall was studying an undergrad in Computer Science at the University of Essex, which he graduated from in 2019.

During his first months at SAS Niall has worked alongside some of the largest organisations within the UK showcasing his strong technical and consulting abilities.

Niall works within the Data science team, mainly focusing on analytics, cloud computing and computer vision.