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.
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.
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.
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, 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.
In this session, we will discover how to utilize common machine learning approaches for daily SQL Server DBA tasks.
This short session will cover some scenarios of cleansing data in Power Query using M, Python, or both languages.
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
This session is for all developers who want to learn about the new Dev features and enhancements of SQL Server 2017 and 2019
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.
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.
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
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.
We will review this new feature of ADFv2, do deep dive to understand the mentioned techniques, compare them to SSIS and/or T-SQL and learn how modelled data flow runs Scala behind the scenes.
In this session, we’ll look at the different options within the Cognitive Services suite, show you how to connect to the APIs using Python code, walk through a live bot demo, and build an Azure Cognitive Search index. You should leave this session feeling like you’ve had a jump start to further your AI developer skill set.
An end-to-end solution covering many Azure features
Learn how to make Azure do the work for you by developing smart responses for Azure SQL DB alerts using Automation and Logic Apps.
Organisations need to know how to get started with Artificial Intelligence. This practical session offers organizations, small and large, with a helping hand in practical advice and demos using Microsoft Azure with Open Source technologies.
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