Model deployment is perhaps the most important step in the ML cycle. We have spent a lot of time and effort playing around with different algorithms, training, and tuning our model parameters, so after evaluating its performance and obtaining that long-awaited score, it is time to release it and show our model to the world. However, the statistics show that 60% of the models never make it out into production, mainly because moving the model into a production environment is not simple and requires extra skills. This workshop will explore different deployment scenarios to release our ML into production using Tensorflow and GCP(Google Cloud Platform).
4:45 PM Doors Open & Registration to enter raffles
5:00 PM Welcome by Erisa Terolli, GDG Hoboken Lead and Women Techmakers Ambassador
5:05 PM Talk by Carolina Castro, Developer Relations Program Manager, Google
5:15 PM Workshop - Machine Learning models deployment in Google Cloud by Henry Ruiz
5:55 PM Win prizes in a raffle
6:00 PM Dinner and Social Hour
7:00 PM Event Ends
GDE
Machine Learning GDE
Developer Relations Program Manager
Google Developer Expert (GDE) in Machine Learning, Currently working as a Data Scientist and finishing his Ph.D. in Engineering at Texas A&M University. His research has focused on solving agriculture problems using the intersection between Remote sensing, High-throughput computing, Machine learning, and deep learning. Full-stack Python and javascript developer, proficient in .Net, MATLAB, and C++. With experience also working with Ml/Dl libraries such as Tensorflow, PyTorch, Scikit-Learn, Scipy, Dask, Pandas, and Opencv. He enjoys developing open-source solutions focused on computer vision (FalconCV, CVStudio, Rigging.js) and working on social-meaning projects in his free time.
His research areas of interest are applied Geophysics, mathematical simulation, electromagnetism, computer graphics, signal processing, Machine Learning, and Deep Learning.
Stevens Institute of Technology
GDG Organizer
Amazon Inc.
Software Development Engineer
