Designing a Data-Intensive Future - Expert Talk
Explore data landscape evolution, local-first collaboration, and career insights with experts Martin Kleppmann and Jesse Anderson. Gain valuable perspectives on data engineering and software development trends.
Auto Feature Engineering - Rapid Feature Harvesting Using DFS & Data Engineering Techniques
Explore rapid feature harvesting for machine learning using Deep Feature Synthesis and data engineering techniques to accelerate model development and shorten time-to-market.
Making ML Model Error an Information Source
Exploring ML model errors as valuable information sources in mobile networks. Innovative approach to assess configuration changes and their impact on performance indicators.
AIOps and ChatGPT - Preparing for the Next Wave in IT Operations
Explore the integration of AIOps and ChatGPT in IT operations, discussing benefits, challenges, and real-world applications for streamlining work and gaining valuable insights to drive business growth.
Beyond Logs - Real-Time Anomaly Detection with Machine Learning
Explore real-time anomaly detection using machine learning on logs and traces. Learn to treat application data holistically, enabling intelligent monitoring and complex issue identification beyond traditional alerts.
Deciphering Alerts - Make Sense of What Your Software Is Saying
Explore how different parts of the tech stack handle validations and errors, and learn to decipher software messages to improve testing and user experience.
Building a Culture of Experimentation at Pinterest
Discover how Pinterest fosters experimentation culture, avoiding pitfalls and leveraging A/B tests for effective feature measurement. Learn to build tools supporting data-driven decision-making in tech organizations.
DNS Spikes, Strikes, and The Like
Explore DNS query patterns to identify potential threats using unsupervised learning methods. Learn to analyze traffic trends and distinguish malicious domains from benign spikes.
Lessons Learned from Building and Running MHN, the World's Largest Crowd-sourced Honeynet
Explore insights from building the world's largest crowdsourced honeynet. Learn about deploying diverse honeypots globally, analyzing security data, and creating a distributed sensor network for tracking threats.
How to Lie with Statistics - Information Security Edition
Uncover deceptive statistical practices in information security reports. Learn to identify manipulated data, misleading charts, and logical fallacies to critically evaluate security-related statistics and research findings.
Squirrel - A Scalable Secure Two-Party Computation Framework for Training Gradient Boosting Decision Tree
Scalable framework for secure two-party GBDT training on vertically split datasets, featuring novel cryptographic techniques for privacy-preserving machine learning in distributed environments.
DScope - A Cloud-Native Internet Telescope
Explore DScope, a scalable cloud-based Internet telescope for monitoring malicious behavior. Learn about its design, implementation, and advantages over traditional methods in capturing cloud-targeting traffic.
Fine-Grained Poisoning Attack to Local Differential Privacy Protocols for Mean and Variance Estimation
Explores a new fine-grained attack on local differential privacy protocols, allowing manipulation of mean and variance estimations. Discusses security-privacy consistency and proposes a defense method.
Apache Pulsar - The Next Gen Messaging & Queuing System
Explore Apache Pulsar's innovative architecture for scalable messaging and queuing, featuring unified flexibility, durability, and serverless processing capabilities for modern data-driven applications.
Unveiling Much Simplified Functional Programming in Scala for Data Engineering
Simplified functional programming in Scala for data engineering, focusing on feature generation abstraction and optimization techniques without complex libraries or boilerplate code.
Speeding Up Innovation
Explore best practices in continuous delivery, cloud-native serverless applications, and chaos engineering to optimize time-to-value and ensure resilience in strategic workloads.
How to Be a More Impactful Data Analyst
Learn strategies to scale your impact as a data analyst by applying software engineering best practices, improving workflows, and transforming your analytics career.
Why Data Science and UX Research Should Be Best Friends
Explore how Data Science enhances UX research through quantitative and qualitative methods, with real-world examples from top companies. Learn to identify collaboration opportunities between these fields.
How to Create & Develop High-performing Data Science Teams
Insights on building effective data science teams: skill mix, culture, and value creation. Learn strategies for recruiting, developing, and embedding high-performing analytics teams in organizations.
It's a Kind Of Magic - Computation on Ciphertexts
Explore practical applications of computing on encrypted data, including cross-organizational data collaboration, through demonstrations and real-world use cases in this insightful presentation.
Predicting F1 Race Strategies using ML.NET
Explore ML.NET for predicting F1 race strategies. Learn to analyze historical data and make informed predictions about team decisions in upcoming Grand Prix events.