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9th edition of Big Data Tech Warsaw Summit 2023!
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and listen to the top rated experts
9th edition of Big Data Tech Warsaw Summit 2023!
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How to start with Azure OpenAI?
GPT family of models is taking over the world by storm. And using them has never been easier – Azure is offering OpenAI as a generally available managed service. But how can we start using it and infuse our solutions with generative intelligence? This session will answer this question along with addressing: what exactly is available on Azure from the OpenAI suite? What models should we use and when? And how can we work with, and integrate, this service in our development process?
#Microsoft #MicrosoftAI #microsoftopenai #openai #azureai
Quality Over Quantity - Active Learning Behind the Scenes
Active Learning - a way for collecting labeled data wisely, thus achieving equivalent or better performance levels with fewer data samples and saving time and money.
Background - what type of methods there is? What is the motivation behind using active learning?
Methods - two different methods will be describe, be demonstrating them on a specific real world use case
Results - what are the results of those methods compared to regular random sampling?
Validations - how can we validate the results? How can we be sure that all the components behaves as we want?
Background - what type of methods there is? What is the motivation behind using active learning?
Methods - two different methods will be describe, be demonstrating them on a specific real world use case
Results - what are the results of those methods compared to regular random sampling?
Validations - how can we validate the results? How can we be sure that all the components behaves as we want?
#activelearning #machinelearning #deeplearning #wisesampling
Quality Over Quantity - Active Learning Behind the Scenes
Active Learning - a way for collecting labeled data wisely, thus achieving equivalent or better performance levels with fewer data samples and saving time and money.
Background - what type of methods there is? What is the motivation behind using active learning?
Methods - two different methods will be describe, be demonstrating them on a specific real world use case
Results - what are the results of those methods compared to regular random sampling?
Validations - how can we validate the results? How can we be sure that all the components behaves as we want?
Background - what type of methods there is? What is the motivation behind using active learning?
Methods - two different methods will be describe, be demonstrating them on a specific real world use case
Results - what are the results of those methods compared to regular random sampling?
Validations - how can we validate the results? How can we be sure that all the components behaves as we want?
#activelearning #machinelearning #deeplearning #wisesampling
An open standard for data lineage
If a job fails, how can you learn about downstream datasets that have become out-of-date? Can you be confident that jobs are consuming fresh, high-quality data from their upstream sources? How might you predict the impact of a planned change on distant corners of the pipeline? These questions become easier once you have a complete understanding of data lineage, the complex set of relationships between all of your jobs and datasets. In this talk, Ross Turk from Astronomer will provide an introduction to the core concepts behind OpenLineage, an open standard for data lineage, and discuss various tactics for using it.
#openlineage, #datalineage, #datagovernance, #openstandards