Jernej Kavka
Microsoft AI MVP, SSW Solution Architect
Microsoft AI MVP, SSW Solution Architect
Brisbane, Australia
Jernej Kavka (JK) is a Microsoft AI MVP, SSW Solution Architect, and organizer of several user groups like AI Hack Days and Global AI The Podcast. JK is a full-stack .NET developer, but his passion lies in Azure Cognitive Services, AI and machine learning. He is the main architect behind SSW's virtual receptionist - SophieAI: https://sswsophie.com
He is also very active in the developer community and enjoys speaking at conferences like NDC, DDD, as well as User Groups and Hack Days.
Jernej ima več 10 let izkušenj s razvijanjem aplikacij za velika podjetja v Avstraliji kot tudi v Sloveniji.
Trenutna orodja za razvoj so .NET Core, Angular, EF Core in Microsoft Cognitive Services.
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How to keep your email tidy with AI
Remote work is becoming a new norm since the pandemic. It has brought a lot of benefits to modern work, but it didn't come at a low cost.
For some, this meant a mountain of never-ending emails, and suddenly, a zero email inbox became an impossible dream.
Depending on the organization, employees can spend hours on emails every week, or even every day. Plus, the statistics for writing emails are not any less terrifying.
Let's see how to use AI to cut through email:
- Find out quickly what are the important messages using AI
- Learn how to automate your emails in a time-efficient way
- Enable yourself to go back to work with automation
We'll look at how we can prototype a few AI models with simple tools like ML.NET, Cognitive Services and Open AI. We'll start with classifying emails and end with proposed actions for your emails.
Common mistakes in EF Core
When JK worked with many different clients and projects, he frequently heard "EF Core is slow" or "We should do this in raw SQL" only to realize they haven't used EF Core correctly.
JK will show you how to improve your EF Core statements as well as how various configurations impacts the performance and scalability of your application. You'll be blown away at how small changes can significantly impact not only the performance but also stability of the application.
Getting Started with Machine Learning using ML.NET
Want to get started with machine learning but don't know where to start? Have you got an Excel spreadsheet, SQL Database or CSV lying around and wondering if you can use it to experiment with Machine Learning?
In this workshop, we'll start from a CSV exported by a service, and go all the way to an application that uses Machine Learning to make clever decisions.
We will cover:
1. What does a developer need to know about Machine Learning?
2. How does ML.NET help getting started with ML?
3. Quickly prototype a solution with ML.NET Model Builder
4. Improve solution with simple data science rules
5. Integrate a machine learning solution into your application
6. Continuously improving machine learning model and updating applications
From Paper to Power using Azure Form Recognizer
Are you still collecting your feedback on paper handouts? Red, yellow, green feedback is faster, but what do you do with that? It’s so time-consuming to go through the feedback forms afterward and maybe you just don’t bother. What if you could collect feedback on a custom form, collate the data and get actionable results before your coffee gets cold?
Join me on the journey from waiting weeks to get feedback from the user group talks to have the results in less than an hour for each event. You’ll see how you can use Form Recognizer to parse the data straight from the page, what you can and can’t do right now, as well as how you can leverage other Cognitive Services to get more details from the user feedback forms!
Making unit tests simple again with .Net Core and EF Core
Unit testing can be hard especially when databases are involved.
In this talk, JK will teach you how to include EF Core to simplify testing of “Will this actually work on a real DB” while keeping the tests self-contained and repeatable.
Also walk away knowing how cool the combination of EF Core in-memory and the SQLite DB provider is.
Real-time Face Recognition With Microsoft Cognitive Services
This session is all about Microsoft Face API in practice!
JK the man behind sswSophie.com will cover what it means to use Microsoft Cognitive Services in real-time, why offline detection libraries are essential and why you should use infrared and depth cameras like Kinect and Intel RealSense in your applications.
Machine Learning simplified for Developers with ML.NET
Do you want to try machine learning, but don't want to invest too much time learning a new programming language or some other complicated API?
Microsoft recently launched ML.NET 1.4 which is a great entry point for .NET developers and to gain experience building something with Machine Learning.
With the recent release of ML.NET Model Builder, we can create machine learning models by attempting to import raw data first and over time curate the data, to get better results.
JK will show you how ML.NET works, how to leverage Model Builder, experiment with training data and what to watch out for when building models.
Jernej Kavka
Microsoft AI MVP, SSW Solution Architect
Brisbane, Australia