Cloud Threats 2023 - A Year in Review
Explore 2023's cloud cybersecurity landscape, analyzing evolving threats and gaining actionable insights for defending organizations against emerging risks.
Brain Embrace Care: Investigating Brain Health Awareness and Lifestyle Medicine in Young Adults with Stroke or TIA - McCance Seminar Series
Explore brain health awareness and lifestyle medicine for young adults with stroke or high-risk TIA through a mixed-methods quality improvement project.
Genes, Family Trees, and Complex Disease
Explore genetics, family history, and disease risk. Learn about genetic testing and environmental factors in complex diseases.
Diabetes Overview: Types, Nutrition, and Treatment Options
Explore types of diabetes, nutrition's role in treatment, and blood sugar management for improved diabetes control.
Climate Change and Vulnerabilities of Pediatric Populations
Explore climate change's impact on children's health and learn strategies to mitigate risks for young populations.
Evolve from Visibility to Actionability - Proactive Measures for Emerging Threats
Discover best practices for managing cloud-based assets and systems, focusing on proactive measures to address emerging threats and enhance security posture.
Burning Fossil Fuels, Climate Change, and Workers - What Clinicians Need to Know
Identify occupational risks from climate change and learn practical strategies for prevention and intervention in patient care.
Tips for Promoting Safe Video Game and Digital Media Use Habits - Blum Center Program
Discover strategies for fostering healthy digital media habits in children, focusing on video games and internet use. Learn to balance screen time with overall well-being.
What's Next in NanoEHS - Risk Assessment and Risk Management
Explore risk assessment and management in nanotechnology environmental health and safety, focusing on future developments and strategies.
Build High Performance MLOps With ML Monitoring and AI Explainability
Discover techniques for enhancing MLOps through ML monitoring and AI explainability. Learn to identify model failures, address operational issues, and streamline model deployment using advanced analytics.
Shopping Recommendations at Pinterest
Explore Pinterest's shopping recommendation systems, from candidate generation to serving methods for diverse recommenders and neural network ranking models.
The Ops in MLOps: Creating Cost-Effective and Compliant ML Environments
Explore techniques for creating cost-effective, secure, and compliant ML environments with proper data governance in MLOps.
Best Practices for Deploying MLOps Solutions in Enterprise
Explore best practices for deploying MLOps solutions in enterprise environments. Learn from industry experts about common pitfalls, avoidance strategies, and early adoption techniques for model lifecycle management.
Continuously Improving Large Scale Recommenders with MLOps Tools and Practices
Leverage MLOps tools and practices to operationalize and continuously improve recommendation systems at scale using NVIDIA Merlin and Kubeflow on Google Kubernetes Engine.
Scaling ML Embedding Models to Serve a Billion Queries
Learn to scale ML embedding models for visual search, exploring eBay's architecture, workflows, and solutions to handle billions of queries efficiently.
Shopify's Machine Learning Platform Journey: Building Merlin with Open Source Tools
Explore Shopify's journey in building Merlin, an open-source ML platform. Gain insights into the architecture, technologies, and tools used to scale machine learning work effectively.
Trustworthy AI for MLOps
Explore strategies for implementing trustworthy AI in MLOps, addressing operational challenges, and fostering transparency to turn AI into a business advantage.
ML Observability: A Critical Piece in the ML Stack
Explore ML Observability's role in addressing model failures, monitoring performance, and improving models. Learn industry best practices for enhancing your ML stack's reliability and efficiency.
How to Treat Your Data Platform Like a Product - 5 Key Best Practices
Discover 5 key best practices for treating your data platform as a product, ensuring reliability and scalability for maximum business value.
Implementing SecMLOps at Every Stage of the ML Pipeline
Implement SecMLOps at every stage of the ML pipeline to address security challenges, comply with data privacy laws, and ensure robust ML system architecture.
Deploying and Managing Machine Learning Models at Scale - A Hands-On Workshop
Deploy and manage ML models at scale. Hands-on workshop covers creation, deployment, monitoring, and management using real-life scenarios. Gain practical experience with Seldon Deploy, explainers, and outlier detection.