A GitOps Approach to Machine Learning in Production
Explore GitOps principles for ML in production. Learn to apply GitOps to deployment, onboarding, monitoring, and model lifecycle stages for enhanced traceability and productivity.
It's All About the Data - Continuously Improve ML Models the Data-Centric Way
Explore data-centric AI practices to enhance ML model performance. Debug input data, analyze datasets, and identify post-deployment issues using open-source whylogs for continuous improvement.
Becoming an ML Platform Power Builder with ML Observability
Discover best practices for building effective ML platforms. Learn key components, justification strategies, and how ML infrastructure differs from software infrastructure.
CyclOps: A Framework for Data Extraction, Model Evaluation and Drift Detection in Clinical Machine Learning
Explore CyclOps, a unified framework for healthcare ML, enabling data extraction, model evaluation, and drift detection in clinical settings. Streamline development of robust AI models.
Airflow: Where Data Engineers and ML Engineers Meet
Explore Apache Airflow's role in operational machine learning with a real-world demo and reference implementation of GenAI in production.
Scouter Models for Concept Drift Detection in MLOps
Explore techniques for detecting concept drift in ML models without true labels using Scouter models. Learn to build, manage, and implement this critical MLOps monitoring strategy.
A Kafka Producer's Request: From Send() to Disk and Back
Explore the lifecycle of Kafka producer requests, from initial call to disk storage and back, enhancing your debugging and performance analysis skills for Apache Kafka.
Serialization - A New Hope: A Data-Oriented Approach
Explore a data-oriented approach to Java serialization, addressing modern requirements and leveraging recent language enhancements for safer, more flexible object externalization.
Introduction to Model Deployment with Ray Serve
Learn to deploy ML models using Ray Serve. Explore Ray Core APIs, create scalable architectures, and integrate with MLflow and FastAPI. Gain hands-on experience in distributed computing and model deployment.
Concept Maps Using C++23 Library Tech - Indirection to APIs for a Concept - Lecture
Explore concept maps in C++23, using inline variable templates to achieve benefits similar to C++0x Concepts. Learn advanced techniques for implementing flexible data structures with monoid-based tags.
Reading Alan Turing - Exploring Turing's Influential Ideas in Theoretical Computer Science
Explore Turing's influential papers and their impact on theoretical computer science with Avi Wigderson. Gain insights into Turing's visionary ideas and their modern relevance.
The World Is Worth How Many APIs? A Thought Experiment
Explore a thought experiment on the number of APIs needed for versatile AI agents in physical environments, using wikiHow tutorials to induce and analyze a rich action space.
Extracting Social Determinants of Health: Annotation, Extraction, and Ethical Considerations - Informatics Grand Rounds
Explore social determinants of health extraction from EHRs using NLP, focusing on annotation, information gain, and ethical considerations in healthcare data analysis.
Using Multiple LLMs in Java with Spring AI
Integrate multiple LLMs in Java using Spring AI. Learn to configure and utilize OpenAI's GPT-4 and Anthropic's Claude 3.5 Sonnet in a single Spring Boot project.
Data and AI World Tour 2024 Bangkok - Deep Dive on Data Management, AI, and Industry Applications
Explore cutting-edge data and AI technologies, real-world applications, and industry insights from global experts. Gain knowledge on generative AI, data governance, and optimizing data intelligence for enterprise success.
Adapting Adam Ferriss' Churning Hue Cycle Shader in TouchDesigner
Adapt Adam Ferriss' "churning hue cycle" shader for TouchDesigner. Learn to modify GLSL code, add uniforms, and integrate Shadertoy shaders into TouchDesigner projects for dynamic visual effects.
Large Language Models and Future of Information Retrieval: Opportunities and Challenges - Lecture 1
Explore the impact of large language models on information retrieval, discussing future opportunities and challenges in search technology.
An Empirical Analysis on Multi-turn Conversational Recommender Systems - Lecture 3.2
Explore multi-turn conversational recommender systems through empirical analysis, examining their effectiveness and potential improvements in interactive recommendation scenarios.
Towards Human-centered Proactive Conversational Agents - Conversational IR and Recommendation
Explore human-centered proactive conversational agents in IR and recommendation systems, focusing on advancements and challenges in creating more intuitive AI interactions.
Search Engine for Machines: Unified Ranking for Multi-Retrieval-Augmented LLMs - Lecture 1
Explore unified ranking for multi-retrieval-augmented LLMs, advancing search engines for machines and enhancing Retrieval Augmented Generation techniques.
LLM-Augmented Dialogue Construction for Personalized Multi-Session Conversational Search - Session M3.2
Explore LLM-augmented dialogue construction for personalized multi-session conversational search, enhancing IR and recommendation systems.