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Metrics-Driven Machine Learning Development at Salesforce Einstein
Eric Wayman discusses how Salesforce tracks data and modeling metrics in the pipeline to identify data and modeling issues and to raise alerts for issues affecting models running in production.
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Building a Voice Assistant for Enterprise
Manju Vijayakumar talks about Einstein Assistant - an AI Voice assistant for enterprises that enables users to "Talk to Salesforce".
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Designing Automated Pipelines for Unseen Custom Data
Kevin Moore discusses some challenges in designing automated machine learning pipelines that can deal with custom user data that it has never seen before, as well as some of Salesforce’s solutions.
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Implementing AutoML Techniques at Salesforce Scale
Matthew Tovbin shows how to build ML models using AutoML (Salesforce), including techniques for automatic data processing, feature generation, model selection, hyperparameter tuning and evaluation.
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Models in Minutes not Months: AI as Microservices
Sarah Aerni talks about how Salesforce built an AI platform that scales to thousands of customers.
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The Black Swan of Perfectly Interpretable Models
Mayukh Bhaowal, Leah McGuire discuss how Salesforce Einstein made ML more transparent and less of a black box, and how they managed to drive wider adoption of ML.
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Managing Thousands of Data Services @Heroku
Gabriel Enslein discusses the evolution of fleet orchestration, immutable infrastructure, security auditing for managing data services for many Salesforce customers.
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The Lego Model for Machine Learning Pipelines
Leah McGuire describes the machine learning platform Salesforce wrote on top of Spark to modularize data cleaning and feature engineering.
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The Cloud Silver Bullet: Which Caliber Is Right for Me?
Chris Read takes a look at clouds from the operations perspective, presenting various types of clouds and their tradeoffs, and the process change the organization needs to go through.
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The Internal Design of Force.com’s Multi-Tenant Architecture
Craig Weissman, Chief Software Architect at Salesforce.com, presents their multi-tenant architecture, one shared database and one application stack, that has proven to scale well over the years.
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Application Services on the Web: SalesForce.com
Dave Carroll describes Force.com as a platform for creating enterprise applications in the Cloud using web service APIs, server side logic, service oriented application support and ALM services.