Speaker: Pitambar Dayal
Affiliation: Application Support Engineer, Mathworks
Hosted by: IEEE Photonics Society Los Angeles Chapter
Abstract: Deep learning achieves human-like accuracy for many tasks considered algorithmically unsolvable with traditional machine learning. It is frequently used to develop applications such as face recognition, automated driving, and image classification.
In this hands-on workshop, you will write code and use MATLAB to:
- Learn the fundamentals of deep learning and understand terms like “layers”, “networks”, and “loss”.
- Build a deep network that can classify your own handwritten digits.
- Access and explore various pre-trained models.
- Use transfer learning to build a network that classifies different types of food.
- Use LSTM networks for time series forecasting.
- Train deep learning networks on GPUs in the cloud.
- Learn how to use code generation technology to accelerate inference performance.
- Learn how to improve the accuracy of deep networks.
Biography: Pitambar works on deep learning and computer vision applications in technical marketing at MathWorks. Prior to joining MathWorks, he worked on creating technological healthcare solutions for developing countries and researching the diagnosis and treatment of ischemic stroke patients. Pitambar holds a B.S. in biomedical engineering from the New Jersey Institute of Technology.
bring a fully charged laptop with Google Chrome installed and a charger.
For more information, contact Cejo Konuparamban Lonappan, Chair, IEEE Photonics Society Los Angeles Chapter (firstname.lastname@example.org)
Date(s) - Mar 12, 2019
1:15 pm - 4:30 pm
EE-IV Shannon Room #54-134
420 Westwood Plaza - 5th Flr., Los Angeles CA 90095