At Very, we strive to produce market ready products with every iteration of a project we work on. This goal is shared across the board, regardless of the product, including our data science engagements. But how do we do that exactly? Jeff McGehee, director of engineering at Very, will shed light on that very topic at the MLConf, on November 14th, 2018 in San Francisco.
Jeff's talk will explain howVery adapts practices from software engineering and design to our data science projects to develop and deploy models quickly. While data science is often seen as a slower field of study, at Very, we’ve developed techniques and too
ls to allow us to produce not only quality data, but quality data quickly.
About the Event
MLConf is a single-day, single-track event that will host a variety of relevant presentations of today’s application of machine learning techniques and algorithms from experts from Google Brain, Uber, Facebook, Baidu, Tesla, and more. The event will host presentations on novel applications of machine learning within real-world arenas such as: geospatial data, cancer metastasis detection, various NLP challenges, and more. The event will take place at Hotel Nikko, 222 Mason Street, San Francisco, CA 94102.
About the Speaker
As a Senior Data Scientist and IoT Practice Lead, Jeff is well-versed in many of the competencies we apply on our projects. Jeff holds a BS in Mechanical Engineering from Tennessee Tech University, an MS in Mechanical Engineering from Tennessee Tech University, and an MS in Computer Science with a focus in Machine Learning from Georgia Institute of Technology. He also holds a patent for his work on computer-implemented intelligent alignment method for color sensing devices.