Anahita Bhiwandiwalla

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Anahita Bhiwandiwalla

Intel Corporation

Biography

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.

Proposals for this user

* Anomaly detection on earthquake data using the 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 uses TAP to detect anomalies in earthquake data and indicate any outliers on real time data. http://trustedanalytics.github.io/
Theory 2016-04-21 00:14:43 +0000
Anahita Bhiwandiwalla, Fred Magnotta, Jitendra Patil

* Automatic model selection and parameter selection with the 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 uses TAP to address two very common questions arising in data science– ‘Which model best fits my data?’ and ‘How do I find the optimal parameters for my models?’ http://trustedanalytics.github.io/
Practice 2016-04-20 18:35:09 +0000
Anahita Bhiwandiwalla

* 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. http://trustedanalytics.github.io/
Theory 2016-04-20 23:46:52 +0000
Anahita Bhiwandiwalla, Fred Magnotta, Jitendra Patil

* Surviving survival analysis with Apache Spark

Learn about survival analysis in Apache Spark and some questions it can help answer. For instance, what proportion of individuals can be affected by a phenomenon, at what rate will they be affected, how certain events affect the probability of survival. http://trustedanalytics.github.io/
Practice 2016-04-20 18:52:59 +0000
Anahita Bhiwandiwalla