Automatic Infrastructure Rightsizing with Dynatrace Workflows - Tips and Tricks 13
Optimize infrastructure using Dynatrace Automation Workflows. Learn to detect improperly sized hosts, trigger approvals, and automate rightsizing across various platforms.
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.
Next-Gen AI Processors and Why We Need to Think Differently About Software 2.0
Explore next-gen AI processors, computational challenges in machine learning, and innovative approaches to efficient processing beyond traditional GPU solutions.
How Not to Let Your Data and Model Drift Away Silently
Discover strategies to prevent data and model drift, ensuring ML models maintain performance and value over time in production environments.
From Concept to Production: Building a Production-Ready ML Pipeline - Part 2
Develop a production-ready ML pipeline from concept to deployment using Python, Kubeflow, and Google Cloud Platform. Master data prep, model training, and orchestration techniques.
MLOps vs ModelOps - Differences, Importance, and Best Practices
Explore the differences between MLOps and ModelOps, focusing on continuous monitoring, automated remediation, and feedback loops for AI and analytical models in enterprise settings.
Multi-armed Bandits in Production at Stitch Fix
Explore scaling challenges and solutions for multi-armed bandits in online experimentation, including a new method for efficient, deterministic Thompson sampling at Stitch Fix.
Taking Aim at Bias in AI - Workshop Sessions
Explore strategies to identify and mitigate bias in AI systems, enhancing fairness and ethical decision-making in machine learning applications.
Building Pipelines with Kubeflow - Hands-on Workshop
Discover Kubeflow pipelines: create environments, build and upload pipelines, and set up retraining schedules in this hands-on workshop for MLOps practitioners.
HoloClean and Kamino - Structured Learning for Private Data Generation
Explore structured learning for private data generation using HoloClean and Kamino frameworks. Learn to preserve data correlations while ensuring privacy in synthetic data instances.
Machine Learning Optimizations and Strategy for Post-Covid Era
Explore ML risk mitigation techniques for post-pandemic model deployment, monitoring, and recalibration across industries, with focus on ethical practices and automated AI/ML solutions.
Security Audits for Machine Learning Attacks
Explore common machine learning security attacks and learn effective remediation strategies to protect your models from harmful outcomes and data exposure. Enhance your organization's security practices.
5 Governance Capabilities You Need in MLOps - Workshop Session
Explore 5 essential MLOps governance capabilities to effectively implement and control machine learning models in production environments. Gain insights on assessing organizational maturity and achieving full MLOps maturity.
Challenges for ML Operations in a Fast Growing Company
Explore ML operations challenges in rapidly growing companies. Learn strategies for scalable platforms, efficient model training, and balancing distributed vs. non-distributed applications. Gain insights on developer ergonomics and best practices.
Machine Learning on Dynamic Graphs - Temporal Graph Networks
Explore Temporal Graph Networks for dynamic graph analysis, unlocking insights in evolving systems like social networks and financial transactions.
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.
The Observability Guide to Platform Engineering - Platform Observability and Success KPIs - Part 1
Explore Internal Development Platforms (IDPs) architecture, success KPIs, and observability practices. Learn to measure adoption, define SLOs, and implement metrics for efficient platform engineering.
Hands-On Behavior Analytics with Dynatrace - A Practical Guide
Explore behavior analytics in Dynatrace, learning to track user journeys, set conversion goals, and optimize digital experiences using tools like Hyperlyzer and Session Replay.
Monitoring Azure Functions with Dynatrace
Explore Azure Functions monitoring with Dynatrace, covering AppService and Consumption plans. Learn to optimize serverless computing performance and integrate systems effectively.
TTP-based Threat Hunting with Security Analytics and Falco Alerts
Explore attacker techniques and defender strategies using Unguard. Learn to conduct reconnaissance, gain access, and achieve persistence. Discover how to detect compromises with Dynatrace and Falco for real-time monitoring and forensic analysis.