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A Python primer for DBAs, how to talk to a SQL Server Andre Kamman
Tinkered with Powershell but not with Python yet? Let's get you started, and we'll do that with some practical examples focussed around talking to SQL Server and importing and exporting some data.
Art of Feature Engineering- For Machine Learning Sandip Pani
The most challenging area of machine learning are Data acquisition, Feature extraction, Feature Selection. Almost in all data science project, 80% of time people spend in Data acquisition and Feature engineering.
Azure AI, Power new possibilities for every organization Lindsey Allen
AI and data is at the center of the digital feedback loops. We have invested in a comprehensive portfolio of AI tools, infrastructure and services. Come to this session to get an update of Azure AI with demos.
Data Exploration & Experimentation with Notebooks in Azure Ian Griffiths
Learn how Azure supports interactive, exploratory notebooks (e.g. Jupyter) for data processing and experimentation across a range of scales from simple single-computer work up to massively parallel Databricks clusters.
Databricks, Delta Lake and You Simon Whiteley
Databricks, Lakes & Parquet are a match made in heaven, but explode with extra power when using Delta Lake. This session will dive into the details of how Databricks Delta works and how to make the most of it.
First Dates: AI & DBAs. Any Chance to be a perfect match? Sascha Lorenz
In this session, we will discover how to utilize common machine learning approaches for daily SQL Server DBA tasks.
Lets do the cleansing with M and / or Python languages Ana Maria Bisbe York
This short session will cover some scenarios of cleansing data in Power Query using M, Python, or both languages.
Machine Learning in Azure Databricks Terry McCann
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
New SQL Server Features for Developers Hasan Savran
This session is for all developers who want to learn about the new Dev features and enhancements of SQL Server 2017 and 2019
Predictive Maintenance with Azure Synapse James Broome
This session provides an end-to-end walk through of how to use Azure Synapse for cloud-hosted advanced analytics, based around a real-world predictive maintenance use case.
Rapid Requirements: Introducing the Machine Learning Canvas Terry McCann
In this session, we will introduce the Advancing Analytics Machine Learning Canvas and how it can be used to capture requirements for Machine Learning Projects.
Taking Models to the Next Level with Azure Machine Learning Amy Boyd
Learn how Tailwind Traders data science team uses Azure Machine Learning features and services to create bespoke open source NLP models and optimise them. Includes Automated ML, Azure ML SDK and Hyperparameter tuning
The Azure Spark Showdown - Databricks VS Synapse Analytics Simon Whiteley
Azure now has two slick, platform-as-a-service spark offerings, but which one should you choose? A separate specialist tools or a one-size-fits-all solution? Join Simon as he compares and contrasts the spark offerings.
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