Most Active Speaker

Jernej Kavka

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.

Awards

Area of Expertise

  • Information & Communications Technology

Topics

  • .net core
  • Azure Cognitive Services
  • Testing
  • Entity Framework
  • ai

The Harmonious Dance of EF Core and SQL Server

In this talk, we'll explore practical strategies to enhance how EF Core and SQL Server work together.

We will delve into effective logging practices, decoding EF Core generated SQL queries, adding indexing and many more.

From Raw Data to Actionable Data with ChatGPT and plugins simplified

In the new era of ChatGPT, Machine Learning and other AI technologies, many things have changed. Developers can now use AI to generate code, social media can be automated and we summarise an entire book in a matter of minutes.

But can we take some data and get some insights out of them? Do we still need to learn a lot of data science, to clean up data? Can AI do my taxes?

Is ChatGPT going to take away my job? Probably not on the last question, but let's have fun and see how far we can push ChatGPT and plugins without a lot of data science knowledge. :)

🤖 ML.NET in the Post-GPT Era: Importance of Machine Learning 🌐

Image Ever thought about machine learning's place in the post-GPT world? 🤖🌐
Get ready for a fun exploration of traditional machine learning, zooming in on ML.NET, in this amazing ChatGPT era.
 
We'll uncover the cool perks and real-life uses of ML.NET, with a relatable example of categorizing bank transactions, and even show you how to level up the process with ChatGPT. Whether you're an AI/ML guru or just getting started, this talk is perfect for everyone. Join us for an exciting learning adventure! 🎉💡

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

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.

NDC London 2024

January 2024 London, United Kingdom

Level Up Your Data

November 2023 Brisbane, Australia

NDC Porto 2023

October 2023 Porto, Portugal

Data, Power BI and AI Bootcamp - Brisbane 2023

June 2023 Brisbane, Australia

NDC Oslo 2023

May 2023 Oslo, Norway

Data, Power BI and AI Bootcamp - Brisbane 2022

November 2022 Brisbane, Australia

NDC Sydney 2022

October 2022 Sydney, Australia

Data and AI Bootcamp - Brisbane 2021

November 2021 Brisbane, Australia

NDC Sydney 2021

November 2021

NDC Sydney 2020

October 2020 Sydney, Australia

Global Azure Virtual

April 2020 Seattle, Washington, United States

NDC Porto 2020

April 2020 Porto, Portugal

Global AI Bootcamp - Brisbane 2019

December 2019 Brisbane, Australia

NDC Sydney 2019

October 2019 Sydney, Australia

DDD Sydney 2019

September 2019 Sydney, Australia

DDD Melbourne 2019

August 2019 Melbourne, Australia

Brisbane Azure Global Bootcamp 2019

April 2019 Brisbane, Australia

Global AI Bootcamp - Brisbane

December 2018 Brisbane, Australia

DDD Sydney 2018

August 2018 Sydney, Australia

Jernej Kavka

Microsoft AI MVP, SSW Solution Architect

Brisbane, Australia