TDD and Generative AI - A Perfect Pairing?
Explore how generative AI can create code from test cases, combining TDD principles with AI-driven development for rapid prototyping and production-ready solutions.
Kotlin 2.0 and Beyond - New Features and Future Roadmap
Explore Kotlin 2.0's new compiler, performance improvements, and upcoming features like guard conditions and context parameters for enhanced development.
The Pearls and Pitfalls of DateTime
Navigate the treacherous terrain of date and time APIs, exploring common pitfalls and solutions. Gain insights into parsing complex date formats and handling time-related challenges in software development.
Genesis of AI-Generated Tools, Open-Source Projects, and Cutting-Edge Techniques
Explore AI-generated tools, open-source projects, and cutting-edge techniques in this multi-speaker keynote on the Genesis of AI.
Platforms: Build Abstractions, Not Illusions
Explore how to create useful abstractions in complex distributed systems, avoiding dangerous illusions that can lead to disappointments.
Unleashing the Power of Angular: Navigating Latest Releases and Transformations - Devoxx 2023
Explore Angular's latest features, including control flow syntax and Signals, to enhance template design, boost performance, and simplify state management in web development projects.
Open Models: The Secret Weapon for Next-Generation Software
Explore open-source AI models like Google's Gemma and their transformative potential. Learn about types, advantages, integration, and future trends in this rapidly evolving field.
Exploring the Power of ChatGPT: Revolutionizing AI Applications
Unlock ChatGPT's potential in AI applications, from creative tasks to secure software development. Explore its capabilities, security implications, and transformative impact across various industries.
Safely Flying the Generative AI Skies - Managing Risks in AI Coding Tools
Explore risks and strategies for safely managing generative AI coding tools in organizations, supporting innovation while minimizing potential hazards.
Guidelines for Secure AI System Development - CISA and International Partners
Explore CISA's guidelines for secure AI system development, covering design, development, deployment, and operations stages.
Overcoming the Challenges of Building GenAI Apps
Explore challenges and solutions for deploying successful generative AI products, accelerating time-to-market and driving impact.
The Rapid Evolution of the Canonical Stack for Machine Learning
Explore the evolution of AI/ML tech stacks and the emergence of a canonical stack for machine learning, democratizing AI for companies of all sizes.
MLOps with PyCaret - Practical Demo for Data Science Workflows
Supercharge your data science team's productivity with PyCaret, an open-source ML library for efficient model preparation and deployment in Python.
What's New in Dynatrace - Release 1.289
Explore Dynatrace v1.289 updates: breaking changes, platform enhancements, AppSec features, infrastructure improvements, and application observability advancements through live demos and detailed explanations.
Boundless Analytics Powered by DQL and Grail - Live Demo and Production Insights
Explore Grail and DQL's advanced capabilities for data analysis, including schema-on-read, real-time parsing, and joining diverse data types to streamline operations.
Dynatrace Extensions 2.0 for Visual Studio Code - Tutorial and Live Demo
Extend Dynatrace's observability capabilities using Extensions 2.0 framework. Learn to develop, test, and manage extensions with the new Visual Studio Code Add-On through a hands-on Apache Kafka example.
What's New in Dynatrace - Release 1.278
Explore Dynatrace v1.278 updates: new documentation design, Kubernetes ownership features, enhanced OS monitoring, DQL functions, AppSec events, and security dashboards. Includes live demos and resource links.
A Practical Guide to JMX Monitoring with Dynatrace
Explore JMX monitoring with Dynatrace, learning to create extensions using Visual Studio Code Add-On. Master capturing JVM metrics, displaying unified analysis, and implementing automated alerting.
MLOps with Orchestration: Accelerating Deployment of AI - Workshop Sessions
Accelerate AI deployment with MLOps orchestration. Learn to integrate tools, streamline processes, and handle complex use cases for efficient ML application development and continuous delivery in production environments.
Complete ML Lifecycle with MLflow - Learn Its Four Components
Explore MLflow's four components to simplify the machine learning lifecycle, from experimentation to production, enhancing reproducibility and accelerating development.
Introduction to Drifter ML: A Testing Framework for Machine Learning Models
Explore Drifter-ML, a testing framework ensuring ML models meet training assumptions. Learn motivations and practical examples for model testing.