Cloud Native Live - Telegraf Kubernetes Operator
Explore the Telegraf Kubernetes Operator for efficient data collection and monitoring in cloud-native environments.
Building Dynamic Machine Learning Pipelines with KubeDirector
Learn to build dynamic ML pipelines using KubeDirector on Kubernetes. Explore a taxi ride prediction example, from model training to deployment, and discover how KubeDirector's "Connections" feature enables always up-to-date ML models.
Building 12 Factor Streaming Data Apps on Kubernetes
Learn to build secure, resilient Kafka streaming apps on Kubernetes using 12-factor principles. Explore Lenses.io's SQL Engine and overcome deployment challenges for portable, cloud-native applications.
CNCF Webinar - The What's and Why's of Tracing
Explore distributed tracing, its importance in microservices, and OpenTelemetry's role in enhancing observability and debugging in cloud-native environments.
CNCF Member Webinar - DevOps from a Different Data-set
Insights from millions of DevOps workflows revealing key performance metrics, benchmarks, and best practices for software delivery teams to improve efficiency and productivity.
Artificial Intelligence Sparks the Fourth Industrial Revolution
Explore AI's transformative impact on industries like transport, finance, and retail. Learn about key market trends, technologies, and real-world applications from Fortune 500 companies.
Anomaly Detection with Deep Learning: Finding the Needle in the Haystack in the Enterprise
Exploring deep learning applications in anomaly detection for enterprise use cases, including preventative maintenance, network intrusion, and fraud detection, with a production case study.
Making Machine Learning Work for Real Business
Insights on successful machine learning deployment in businesses, covering trends and applications across industries from medical to self-driving cars to sales enablement.
End-to-End Deep Learning Project: Kidney Disease Classification with MLflow, DVC, and Deployment
Comprehensive deep learning project on kidney disease classification, covering data ingestion, model preparation, training, evaluation, MLflow integration, DVC pipeline, and AWS deployment.
Machine Learning - Lecture 10
Explore advanced machine learning concepts and techniques in this comprehensive lecture, focusing on practical applications and theoretical foundations.
White-Box Cryptography - Frameworks, Encoding, and Analysis
Explore white-box cryptography frameworks, encoding techniques, attacks, and analysis methods. Gain insights into incompressibility, mitigation strategies, and future research directions in this field.
Masking Post-Quantum Cryptography - Part I
Explore cutting-edge post-quantum cryptography masking techniques, including zero tests, secure multiplication, and Kyber implementations, presented at CHES 2023.
Introduction to Generative AI and Data Storytelling
Explore how generative AI enhances data storytelling, creating dynamic narratives from complex datasets. Learn techniques to leverage AI for impactful data communication and business efficiency.
Learning from Dependent Data - Lecture 1
Explore techniques for learning from dependent data, focusing on probabilistic and optimization methods in data science. Gain insights into handling interconnected information effectively.
5 Questions to Ask About Your Data for Choosing the Right Tool
Discover key questions to ask about your data's shape, usage, privacy, sensitivity, and volume to choose the right management tools and make informed decisions.
Building Knowledge Graphs
Explore the power of knowledge graphs in data management, their applications, and strategies for successful implementation in semantic search, recommendation systems, and data fabric.
Multi-party Computation I - Session 109
Explore the fundamentals and applications of Multi-party Computation, a cryptographic protocol enabling secure collaborative computations while preserving data privacy.
Differentiable Programming for End-to-End Optimization of Experiments - Lecture 7
Explore differentiable programming for optimizing experiments in high-energy physics. Learn advanced techniques to enhance data analysis and improve experimental design in particle physics research.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 4
Explore advanced machine learning techniques for high energy physics, including Deepsets, Graph Neural Networks, and Transformers, with expert Sanmay Ganguly.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 2
Explore advanced deep learning architectures like Deepsets, Graph Neural Networks, and Transformers for high-energy physics applications in this comprehensive lecture.
Deepsets, Graph Neural Networks, and Transformers in Machine Learning - Lecture 1
Explore advanced machine learning techniques for high-energy physics, including Deepsets, Graph Neural Networks, and Transformers, with expert Sanmay Ganguly.