Drinking From The Firehose of Science: Developments in Semantic Scholar and Scientific Literature Access
Explore recent developments in Semantic Scholar and learn how to leverage its APIs for scientific literature analysis. Discuss strategies to increase diversity in scientific participation.
Should We Teach Machine Learning Systems?
Explore feature engineering and instruction in machine learning to improve AI system output quality and reliability. Contrast with current hands-off learning approaches.
Finding the Bad Guys with AI - Connecting the Dots in Data
Explore AI-powered data analysis for law enforcement, connecting diverse information sources to uncover hidden links. Learn about Paliscope's innovative software and its real-world applications.
GPT-SW3: The First Large Generative Language Model for Nordic Languages
Explore the development and applications of GPT-SW3, the pioneering large generative language model for Swedish, with insights on data challenges and future directions.
Deep Learning Meets Nonparametric Regression: Are Weight-decayed DNNs Locally Adaptive?
Explore deep learning's curve-fitting capabilities, comparing DNNs to classical methods and uncovering insights on their strength, generalization, and the role of sparsity in neural networks.
Cyberinfrastructure Needs for Field Geology - Insights from Yosemite and Owens Valley
Explore challenges and opportunities for AI in field geology through a computer scientist's perspective on a unique interdisciplinary field trip to Yosemite and Owens Valley.
Feature Engineering and Modeling Techniques for Menu Design at HelloFresh
Discover how HelloFresh uses data-driven approaches to optimize menu design, predict recipe performance, and align product offerings with customer preferences and business strategies.
How to Build a Real-Time ML Pipeline for Fraud Prediction
Build a real-time ML pipeline for fraud prediction, addressing challenges in online feature engineering and real-time data ingestion. Learn to generate ML features, use a feature store, and monitor for drift.
Global School Connectivity DataOps Platform
Explore the development of an open-source DataOps stack managing connectivity data for millions of schools, covering ingestion, pipelines, quality, and analytics integration.
Mastering Windows Monitoring in Kubernetes Environments
Implement Windows monitoring in Kubernetes using HostProcess containers, Windows exporter, Prometheus, and Grafana. Learn metric collection, deployment, and analysis for effective Windows node management.
Power Efficiency of Modern Servers
Explore power distribution in servers, analyze efficiency improvements, and examine the impact of inlet temperature changes on data center energy consumption.
OpenTelemetry's Path to Observability's Future
Explore OpenTelemetry's role in shaping observability's future. Learn core concepts, instrumentation, data collection, and industry adoption for enhanced system monitoring and troubleshooting.
Unlocking Insights Through Incident Management Reports
Discover how to leverage incident management reports for valuable insights, improve resource allocation, and enhance customer experience through data-driven decision-making.
Scaling OpenTelemetry Collectors Using Kafka - Conf42 SRE 2024
Learn to scale OpenTelemetry collectors using Kafka for improved observability in large-scale systems. Explore architecture, implementation, and monitoring techniques for efficient data processing and analysis.
The Future of Search - Empowering Semantic Search with LLMs
Explore the evolution of search technology, focusing on vector databases and LLMs. Learn about semantic search setup, real-world applications, and see a practical demonstration.
A Journey into the OpenTelemetry Framework
Explore OpenTelemetry framework's fundamentals, including observability concepts, logs, metrics, and traces. Learn implementation methods and installation options for effective cloud-native monitoring.
Hacking OpenTelemetry - Manipulating Observability Pillars
Explore OpenTelemetry hacking techniques to manipulate observability pillars, transform logs into traces, and optimize data flow for enhanced system monitoring and analysis.
Utilizing the Power of Machine Learning in Healthcare - Heart Failure Prediction
Explore machine learning's potential in healthcare through heart failure prediction, addressing diagnostic limitations and leveraging neural networks with real-world data.
Solving Migration Pipelines
Explore strategies for solving migration pipeline challenges in cloud-native environments, focusing on efficiency and scalability.
PyReason and Abduction for Trajectory Generation
Explore combining PyReason's annotated logic with abductive inference for robust human movement trajectory generation, countering anomaly detection.
Clin-MSI: A Machine Learning-Based Approach to MSI Detection in Endometrial Cancers
Explore a machine learning approach for detecting microsatellite instability in endometrial cancers, enhancing diagnostic accuracy and treatment selection for patients.