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A journey through the Tidyverse Thomas Hütter
An introduction to the philosophy of tidy data and the collection of R packages called Tidyverse that help to treat your data appropriately. Including lots of demos from ingesting to cleaning to visualizing your data.
AI For Good: Cognitive Services Vision Alicia Moniz
Curious about Visual Recognition and Object Detection in Azure? Are you wondering what the difference is between the Computer Vision API and the Custom Vision API? Get up Speed with the Vision API in less than an hour!
AI on Edge, encounter between Data Science and IoT Jean-Pierre Riehl
That session explains how to put AI algorithms on Edge devices, with feedbacks from a computer vision project
The video is not available to view online.
Analyzing database with XE and Query Store data using R / Py Tomaz Kastrun
DBA and Data scientists should work together! Analyzing data gathered with XE and Query Store data using R or Python for better database insight and discovering hidden patterns.
The video is not available to view online.
Artificial Intelligence, Machine Learning and Deep Learning Buck Woody
What is the difference between Artificial Intelligence, Machine Learning and Deep Learning and how can each be used? Join Buck Woody cover simple, clear explanations for these technologies, how they can be applied.
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.
Azure Machine Learning and the Python SDK Robin Lester
Understand how to create, train and operationalize your data science projects in Azure Machine Learning.
Build Killer Knowledge Mining Apps with Cognitive Search Luis Cabrera-Cordon
Come learn how you can convert you data into structured formats, apply machine learning skills and index it to make it easy to find information and relationships that can save you time and money.
Build or buy AI? Steph Locke
If AI is on the cards in your business you might need to make a recommendation as to whether your company should Buy or Build. Come to this session to work out the moving parts to turn "It Depends!" into an answer.
Combatting illegal fishing with Azure for less than £10/mth Carmel Eve
We will see how to construct a cloud-first architecture based on serverless data analytics. We will look at specific challenges and cost saving strategies, to produce a reliable, scalable and cost effective solution!
Common Data Science Mistakes Tomaz Kastrun
Taken from the 20+ years of field experiences, many common statistical and data science mistakes have been detected. Session will tackle couple of them.
The video is not available to view online.
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.
Democratizing Machine Learning on the SQL Platform Michelle Wallig
Come and join us this session to unleash the power from your data as we introduce Machine Learning Services for Python and R across the SQL Platform.
Ethics and Bias in data science Robin Lester
How to understand where bias lies, how to collect data and the impact of bias and ethical considerations in your data science solutions.
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.
How To Start Collaborating With A GitHub Repository Rob Sewell
Wanted to join with open-source projects but don’t know how? This quick session will give you all that you need to start doing so.
Implementing AI using Azure Machine Learning Services Vitor Fava
In this session, we will discuss the basics of IA and how we can apply it in our business using the Azure Machine Learning Services
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 and Power BI Alex Whittles
In this session we’ll look at what ML tools are available in the Power BI and Azure worlds, and how you go about using these in your Power BI reports
Machine Learning in Azure Databricks Terry McCann
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
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