Jernej Kavka
Microsoft AI MVP, SSW Solution Architect
Microsoft AI MVP, SSW Solution Architect
Brisbane, Australia
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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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Unlocking the Power of AI on Azure: A Hands-On OpenAI Workshop
Dive into a comprehensive workshop designed to empower participants with the skills to leverage OpenAI’s cutting-edge technology on Azure. This interactive session offers a hands-on approach, guiding attendees from foundational concepts to advanced real-world applications.
Requirements:
Bring your laptop
Agenda Overview:
Introduction & Overview
Start with an overview of the workshop's objectives and essentials of integrating AI on Azure to set a solid knowledge base.
Configuring Azure for OpenAI
Step-by-step setup to configure Azure for OpenAI usage, including live troubleshooting support for those facing issues.
Exploring GPT Capabilities
Deep dive into the capabilities of GPT-4, exploring its use cases in semantic search, content generation, and beyond. Note: Focus on GPT-4 as GPT-3.5 is being phased out.
DALL-E Image Generation
Experience hands-on training with DALL-E for creating stunning images from text prompts.
Using Your Own Data with Azure OpenAI
Learn best practices for data storage and integration with Azure OpenAI. This includes hands-on practice with data loading and Retrieval-Augmented Generation (RAG) for customized outputs.
Deployment & Real-Time Applications
Gain practical insights into deploying models for real-time applications that can be seamlessly integrated into your projects.
Wrap-Up & Q&A
Conclude with key takeaways, a discussion on next steps, and an open Q&A session to address any outstanding questions.
Leveraging Offline AI with Small Language Models in .NET
Discover how to quickly set up your own offline AI system for conversational interactions or to power your applications—whether at home or in the cloud.
Small Language Models (SLMs) are powerful tools that enable advanced AI capabilities without the need for constant internet connectivity or extensive resources. This talk focuses on the potential of SLMs for offline applications, using home automation as a compelling example. We'll delve into how SLMs work, demystify model naming conventions like 8B, Q4, and more.
Join us to explore the possibilities of offline AI and learn how to implement SLMs effectively for enhanced privacy, efficiency, and control in your projects.
Building solutions in Azure OpenAI
With ChatGPT being more accessible than ever, it's becoming essential to understand how to add AI to our applications and existing flow.
This talk will focus on some of the features Azure OpenAI offers to help your application leverage 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.
Level Up Your Data 2024 Sessionize Event
Data and AI Bootcamp - Brisbane 2024 Sessionize Event
NDC Sydney 2024 Sessionize Event
NDC London 2024 Sessionize Event
DDD Brisbane 2023 Sessionize Event
Level Up Your Data Sessionize Event
NDC Porto 2023 Sessionize Event
Data, Power BI and AI Bootcamp - Brisbane 2023 Sessionize Event
NDC Oslo 2023 Sessionize Event
Data, Power BI and AI Bootcamp - Brisbane 2022 Sessionize Event
Global AI Developers Days Sessionize Event
NDC Sydney 2022 Sessionize Event
Data and AI Bootcamp - Brisbane 2021 Sessionize Event
NDC Sydney 2021 Sessionize Event
The Virtual ML.NET Community Conference 2021 Sessionize Event
NDC Sydney 2020 Sessionize Event
NDC Minnesota 2020 - Online Workshop Event Sessionize Event
Virtual Global AI on Tour 2020 Melbourne Australia Sessionize Event
The Virtual ML.NET Community Conference Sessionize Event
Global Azure Virtual Sessionize Event
NDC Porto 2020 Sessionize Event
Global AI Bootcamp - Brisbane 2019 Sessionize Event
NDC Sydney 2019 Sessionize Event
DDD Sydney 2019 Sessionize Event
DDD Melbourne 2019 Sessionize Event
Brisbane Azure Global Bootcamp 2019 Sessionize Event
Global AI Bootcamp - Brisbane Sessionize Event
DDD Sydney 2018 Sessionize Event
Jernej Kavka
Microsoft AI MVP, SSW Solution Architect
Brisbane, Australia
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