Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA

Nutrition Data Science

Noah Gift (UC Davis ), Michelle Davenport (Quantitative Nutrition)
3:50pm4:30pm Thursday, March 28, 2019
Secondary topics:  Health and Medicine

Who is this presentation for?

Anyone interested in Nutrition and Health



Prerequisite knowledge

Understanding of concepts around notebook based Data Science

What you'll learn

* How to become evolved in the emerging Nutritional Science and Data Science world. * The impact of sugar on health and longevity * The technical details of doing Nutrition Data Science


Nutritional Science and Data Science are two fields on a collision course. The field of Nutrition has been plagued by confusing signals to the public, largely due to statistical limitations and poor data quality, both of which can be enhanced by data science and the collective power of new technologies. We explore the relationship between sugar and longevity, obesity and other chronic diseases, and make predictions based on our current consumption rates.

Below are evolving resources to explore related to the project:

Kaggle Project:

Github project:

Colab Notebook:

Photo of Noah Gift

Noah Gift

UC Davis

Noah Gift is lecturer and consultant at both UC Davis Graduate School of Management MSBA program and the Graduate Data Science program, MSDS, at Northwestern . He is teaching and designing graduate machine learning, AI, Data Science courses and consulting on Machine Learning and Cloud Architecture for students and faculty. These responsibilities including leading a multi-cloud certification initiative for students. He has published close to 100 technical publications including two books on subjects ranging from Cloud Machine Learning to DevOps. Gift received an MBA from UC Davis, a M.S. in Computer Information Systems from Cal State Los Angeles, and a B.S. in Nutritional Science from Cal Poly San Luis Obispo.

Noah is a Python Software Foundation Fellow, AWS Subject Matter Expert (SME) on Machine Learning, AWS Certified Solutions Architect and AWS Academy Accredited Instructor, Google Certified Professional Cloud Architect, Microsoft MTA on Python, and has published books on cloud machine learning and DevOps. He writes and publishes content for publications including Forbes, IBM, Red Hat, Microsoft, O’Reilly, and Pearson. Workshops and Talks have been given around the world for organizations including NASA, PayPal, PyCon, Strata, and FooCamp. As a SME on Machine Learning for AWS, he helped created the AWS Machine Learning certification.

He has worked in roles ranging from CTO, General Manager, Consulting CTO, Consulting Chief Data Scientists and Cloud Architect. This experience has been with a wide variety of companies including ABC, Caltech, Sony Imageworks, Disney Feature Animation, Weta Digital, AT&T, Turner Studios and Linden Lab. In the last ten years, he has been responsible for shipping many new products at multiple companies that generated millions of dollars of revenue and had global scale. Currently he is consulting startups and other companies, on Machine Learning, Cloud Architecture and CTO level consulting as the founder of Pragmatic AI Labs. His most recent book is Pragmatic AI: An introduction to Cloud-Based Machine Learning (Pearson, 2018). His most recent video series is Essential Machine Learning and AI with Python and Jupyter Notebook LiveLessons. It is also available on Safari Online

Photo of Michelle Davenport

Michelle Davenport

Quantitative Nutrition

Michelle Davenport earned her PhD in Nutrition from New York University, and received her clinical training as a registered dietitian from the University of California, San Francisco. Upon returning to her roots in Silicon Valley, Michelle earned her reputation as one of the most sought after nutrition experts in food and tech. Previously the President and Co-founder of Raised Real, she created a venture-funded, tech-driven, subscription food program for children that targets infant nutritional milestones. As the fastest growing kids’ food brand in the US, Raised Real currently delivers to thousands of families nationwide. Prior to Raised Real, she worked as the Director of Nutrition for Zesty (acquired by Square), where she developed the food and nutrition API and a proprietary nutrient analysis program.

Currently Michelle consults startups and larger companies on data science in nutrition data analysis and precision-based methods to food and health product research and development. She also serves as a clinical and scientific advisor to startups, including Ritual, a direct-to-consumer supplement company for women. Michelle and her work has been featured in Fast Company, Forbes, Time, WSJ, among others. She lives in Menlo Park, CA with her husband Josh and daughter Sophie.

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