Personalized wellness recommendation using Trusted Analytics Platform*
Trusted Analytics Platform (TAP) is an open source software, optimized for performance and security, that accelerates the creation of cloud-native applications driven by Big Data Analytics. This talk aims to demonstrate how the Trusted Analytics Platform can be used to make real-time wellness recommendation using live data from your activity tracker.
Trusted Analytics Platform (TAP) is an open source software, optimized for performance and security, that accelerates the creation of cloud-native applications driven by Big Data Analytics.
In this talk, we aim to demonstrate how real-time wellness recommendations can be made using data from a fitness tracker like the Basis Peak or any other similar data source. The application learns activity patterns and make wellness recommendations to the user to help improve performance. For instance, suggesting hydration and snack times pre-workout, or rest intervals for cardiac patients during strenuous periods.
Anahita conducted multiple knowledge sharing talks internally at Intel Corporation.
Conducted a webinar - https://www.brighttalk.com/webcast/10773/192209
Anahita starts presenting at 19:07 mins
Fred has conducted multiple webinars and workshops internally at Intel and externally. Some links to Fred's webinars - https://www.brighttalk.com/webcast/10773/191311
Anahita is a Software Engineer in Intel’s Big Data Solutions group, currently working on the Trusted Analytics Platform. She holds a Master’s degree in Computer Science from Columbia University specialized in Machine Learning. Her main interests are in Machine Learning, Natural Language Processing, Speech Recognition and Data Mining. She is very inclined towards applying various machine learning principles to real world applications and solving challenges that arise as the data scales.
Fred Magnotta is a Senior Engineering Manager in Big Data Solutions within the Datacenter Group of Intel. He has been leading the Development effort of the Intel Analytics Toolkit, since its inception. He focuses on Machine Learning and enabling the Data Scientist to discover hidden relationships within their Big Data. He has over a decade of experience in dealing with large scale data, ranging from satellite terrain data to insurance industry mortality analysis. He has lead teams and companies in delivery of software products that literally 10s of millions of people have used. He has degrees in Computer Science, Mathematics and Information systems management.
Jitendra Patil is a Software Engineer in Big Data Solutions group at Intel Corporation. He is working on Intel’s open source Trusted Analytics Platform (TAP). Jitendra completed his Masters from University of Southern California in Computer Science. Outside of tech he likes to hike and travel.