MLflow 3.0：Databricks 上的 AI 和 MLOps.pdf

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1、Forward-looking StatementThis presentation has been prepared for informational purposes only.The information set forth herein does not purport to be complete or contain all relevant information.Statements contained herein are made as of the date of this presentation unless stated otherwise.This pres

2、entation and the accompanying oral commentary may contain forward-looking statements.In some cases,forward-looking statements can be identified by terms such as“may”,“will”,“should”,“expects”,“plans”,“anticipates”,“could”,“intends”,“projects”,“believes”,“estimates”,“predicts”,or“continue”,or the neg

3、ative of these words or other similar terms or expressions that concern Databricks expectations,strategy,plans,or intentions.Forward-looking statements are based on information available at the time those statements are made and are inherently subject to risks and uncertainties that could cause actu

4、al results to differ materially from those expressed in or suggested by the forward-looking statements.Forward-looking statements should not be read as a guarantee of future performance or outcomes.Except as required by law,Databricks does not undertake any obligation to publicly update or revise an

5、y forward-looking statement,whether as a result of new information,future developments or otherwise.2Complete Your SurveysYou will receive a survey for each session attendedOpen the Databricks Events app and select“My Surveys”from the menuSurveys can also be submitted in the Attendee Portal3Your fee

6、dback has a direct impact on Data+AI Summit contentMLflow 3.0Arpit JasaparaEngineeringCorey ZumarMLflow LeadAI and MLOps on Databricks5Enterprise-gradeOpen sourceIntelligent2018:MLOps for classical models&NNs6Enterprise-gradeOpen sourceIntelligent2023:Train&Tune high-quality LLMsRedesigned forGenAI