Artificial Intelligence Machine Learning Deep Learning Data Sciene Finance
Atlanta, Georgia, United States
Robert holds a M.S. in Computer Science with a specialization in Machine Learning from the Georgia Institute of Technology. He has 30+ years’ experience working with large B2B and B2C projects in several industries in roles ranging from Senior Engineer to Architect. Since joining Veloxiti he has developed deep learning approaches for signal processing and contributed to architectural designs for hybrid intelligent systems for the energy industry. Previously, he held a Research Faculty position at Georgia Tech serving as the Technical Lead on an NSF-backed AI project named VERA. In his free time Robert enjoys exploring bleeding-edge AI solutions, participates in the Erlang Ecosystem Foundation's Machine Learning Working Group, reading high-tech scifi, and binging on Netflix series.
Up to now, most mainstream deep learning (DL) solutions have primarily been built on top of Python (TensorFlow, PyTorch, Keras, etc), and as such have had to work around the limitations of the Python interpreter and ecosystem. Axon is a deep learning framework built in Elixir that can leverage the scalability, distribution, and IO performance of Elixir while providing a functional, elegant and intuitive way to train, test and deploy deep learning models. In this session we will explore Axon, Nx, and Livebook as a deep learning stack in the larger Elixir ecosystem.