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1
Introduction
2
About Azure Systems Lab
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Class of Systems
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Summary
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Insights
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Endtoend platform
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Demo
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Overview
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What is Onyx
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Converting models to Onyx
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Onyx Rebase Optimizer
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Office Team Example
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Integration with Onyx
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Selling the Model
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Store Models in Databases
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Provenance
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Future Work
Description:
Explore an insightful conference talk on automating the machine learning lifecycle using MLflow to improve data scientists' productivity. Discover Flock, an end-to-end platform designed for Enterprise Grade Machine Learning (EGML) applications. Learn how Flock leverages MLflow to simplify and automate crucial steps in the data science process, allowing professionals to focus on model improvement. Delve into Flock's features, including automatic logging, integration with relational databases, model optimizations, and support for ONNX format and runtime. Gain valuable insights into ongoing work on tracking data and ML model lineage, essential for regulated environments. Watch a demonstration of Flock's capabilities using Microsoft's Azure Data Studio and MLflow, and understand how this platform addresses challenges in data handling, model fairness, user privacy, and debuggability in enterprise applications.

Improving the Life of Data Scientists - Automating ML Lifecycle through MLflow

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