Sessions

Henk Boelman
Developers Guide to Azure AI [4-Hour Workshop]
Henk Boelman

After a tremendous age of innovation and research in the AI field, we are moving towards the age of appliance. But how and where do you get started as a developer? In this workshop we dive into the AI platform on Microsoft Azure and find out how you as a developer you can use the power of AI in your

Room: Breakout Room C
Topics: Application Development;
Tags: Azure; Machine Learning

Veronika Kolesnikova
Make your applications interactive with Speech Services
Veronika Kolesnikova

Everyone knows we can’t deny benefits of artificial intelligence both for business and for consumers. Developers are trying to integrate it to all kinds of applications and all major tech companies are working on making it as accessible as possible. Whether you are working with machine learning mode

Room: Breakout Room I
Topics: Application Development;
Tags: Azure; Machine Learning

Luther Hill
Build a Data Pipeline in the cloud for Bird Recognition
Luther Hill

Build a cloud data pipeline to enable bird recognition from streaming video and provide descriptive information about the birds. The architecture will take live streaming video and use lambda functions to initiate image recognition, data mapping, and display the information on a webpage. This projec

Room: Breakout Room G
Topics: ;
Tags: .NET; Architecture; Azure; Machine Learning; Microservices; NoSQL; Python; Serverless; SQL; Windows

Mesut Durukal
Do Bugs Speak?
Mesut Durukal

Do bugs speak? Yes, they do. People speak different languages like English, German, French, Chinese etc. But is communication to bugs possible? It is important to understand them, because they really tell something to us. There are valuable information underlying the bugs of a software, and informat

Room: Breakout Room C
Topics: ;
Tags: Machine Learning; Quality Assurance; Testing

Ron Dagdag
Developing Spidey Senses : Anomaly Detection for apps
Ron Dagdag

Anomaly detection is the process of identifying unexpected items or events in data sets. It’s about detecting the deviation from expected pattern of a dataset. It’s like having “spidey senses” for your apps that can detect when there’s danger or something is not right. Attend this session and learn

Room: Breakout Room I
Topics: Application Development;
Tags: .NET; Azure; Cloud; Machine Learning

Henk Boelman
DevOps and Machine Learning
Henk Boelman

With machine learning becoming more and more an engineering problem the need to track, work together and easily deploy ML experiments with integrated CI/CD tooling is becoming more relevant than ever. In this session we take a deep-dive into the DevOps process that comes with Azure Machine Learning

Room: Breakout Room E
Topics: ;
Tags: Continuous Delivery; DevOps; Machine Learning

Mesut Durukal
Future of Software Testing: Artificial Intelligence Assistance
Mesut Durukal

Nowadays, researches are looking for adaptation of Machine Learning algorithms to testing processes to reduce the manual effort and improve quality. In this talk, we will discuss in detail Machine Learning practices with a case study. We start with a quick view of the machine learning types. Then,

Room: Breakout Room C
Topics: ;
Tags: Machine Learning; Quality Assurance; Testing

Bruno Capuano
Let’s code a drone to follow faces! Using AI, Python, containers and more.
Bruno Capuano

You can control a drone using 20 lines of code. That’s the easy part. However, adding extra features like face or object detection and program the drone to follow and object or a face requires … another 20 lines of code! During this workshop we will review how to connect to a drone, how to send and

Room: Breakout Room J
Topics: Application Development;
Tags: .NET; IoT; Machine Learning; Python

Douglas Starnes
Machine Learning for .NET Folks Without (or With!) a Ph.D.
Douglas Starnes

The modern world has already been impacted by machine learning and will continue to be impacted even more. It is critical that more software developers have access to this skill. With ML.NET, .NET developers are not left out! ML.NET is an open-source and cross platform framework to train custom m

Room: Breakout Room H
Topics: Application Development;
Tags: .NET; Machine Learning

Ron Dagdag
Men from Mars, Women from Venus: both can code .NET in Jupyter
Ron Dagdag

Jupyter Notebook is an open-source web application that allows you to create and share documents that contain live code, equations, visualizations and narrative text. Attend this session and learn how you can write .NET code in Jupyter Notebooks and fall in love with .NET all over again

Room: Breakout Room G
Topics: Application Development;
Tags: .NET; Machine Learning

Ahmed Firjani
Record Linkage and Deduplicating Data with ML
Ahmed Firjani

Machine learning and fuzzy matching can enable us to identify duplicate or linked records across datasets, even when the records don’t have a common unique identifier. Ahmad Firjani will explain how he used machine learning algorithms to link matching records from clinic dataset to other patient da

Room: Breakout Room D
Topics: ;
Tags: Big Data; Database; Machine Learning; People; Python; SQL; Work Skills

About

A software development conference in the Louisville, KY area on August 19 - 21, 2020 designed to cover all aspects of software development regardless of development stack.

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