Dataframes Are All You Need: MLOps on Easy Mode
Explore the power of dataframes in MLOps with Jay Chia. Learn how this flexible abstraction simplifies complex data processing, analytics, and machine learning pipelines using Daft as an example.
From Arduinos to LLMs: Exploring the Spectrum of ML - MLOps Podcast Episode 162
Explore MLOps spectrum from LLMs to TinyML. Gain insights on model deployment challenges, IoT integration, and strategies for constrained environments. Learn about the intersection of machine learning and electronics.
Democratizing AI - Vector Databases and LLM Applications
Explore vector databases, LLM app building, and AI democratization with Yujian Tang. Learn about Milvus, production use cases, data challenges, and the future of AI technologies.
The Emerging Toolkit for Reliable, High-quality LLM Applications
Explore emerging techniques in LLMOps for building, tuning, and maintaining high-quality LLM applications. Learn about testing tools, programming frameworks, and methods to control LLM outputs for desired goals.
Building LLM Applications for Production
Explore key challenges in deploying LLMs to production, covering essential considerations for real-world application development and implementation.
Scalable Evaluation and Serving of Open Source LLMs
Explore challenges and solutions for serving open-source LLMs in production, focusing on scalable evaluation and deployment strategies.
Using Vector Databases: Practical Advice for Production - LLMs in Prod Conference
Explore vector databases for LLMs in production. Learn design patterns, context retrieval, feature injection, and common pitfalls. Gain practical insights for efficient deployment and management.
Understanding the LLM Economics: The $360k Question - Lecture
Explore LLM economics, comparing costs of RAG vs fine-tuning and open-source vs commercial models. Gain insights on optimizing expenses for production-ready LLM applications.
Evaluating LLM-based Applications - Part 2
Learn hands-on techniques for evaluating language models, including data sourcing, automated metrics, and human evaluation. Gain practical tools for assessing LLM-based applications effectively.
Eliminating Garbage In/Garbage Out for Analytics and ML
Discover strategies to eliminate bad data at the source, improve data quality ownership, and enhance observability in Analytics/ML stacks. Learn from experts in data engineering and product management.
Building Products with LLMs in Production - Panel Discussion
Explore key challenges and pitfalls in building LLM-based products, including costs, latency, and effective implementation strategies. Gain insights from industry experts on navigating the complexities of AI development.
Experiment Tracking in the Age of LLMs - MLOps Podcast
Explore experiment tracking in the age of LLMs with Neptune's CEO. Gain insights on managing ML experiments, prompt engineering, and achieving control and confidence in model development.
MLOps at the Age of Generative AI - Podcast Episode 169
Explore MLOps in the era of generative AI with insights on developing, training, and serving large language models. Gain practical knowledge on evaluating use cases and addressing challenges in AI product development.
The Confidence Checklist for LLMs in Production
Discover practical strategies for securing and confidently deploying LLM systems in production, addressing performance, user satisfaction, and system monitoring challenges.
From Virtualization to AI Integration - MLOps Coffee Sessions
Explore AI integration challenges for businesses, from virtualization to modern ML systems. Gain insights on bridging gaps in AI implementation and investment strategies.
Collaboration and Strategy in Data Science and AI - MLOps Podcast
Explore collaboration, strategy, and data monetization in AI. Learn to become a multiplier, leverage effective strategies, and maximize data potential in the generative AI era.
Getting ML Applications Into Production - Expert Roundtable
Explore expert insights on overcoming challenges in ML application production, from organizational structure to tech stack bottlenecks, with practical strategies for efficient deployment.
Building an ML Platform: Insights, Community, and Advocacy - MLOps Coffee Sessions
Explore ML platform development, community building, and advocacy at Wolt. Gain insights on onboarding data scientists, creating user-friendly documentation, and implementing DevRel strategies for effective ML deployments.
Evaluating LLM Applications - Insights from Shahul Es
Explore LLM application evaluation with Shahul Es. Learn about debugging, benchmarks, custom data distributions, and fine-tuning to enhance model performance in this insightful discussion.
MLOps vs ML Orchestration - Exploring Challenges and Community-Driven Development
Explore MLOps vs ML Orchestration with Ketan Umare, discussing Union.AI, Flyte, community-driven development, real-time data handling, and democratizing machine learning for broader accessibility and efficiency.
Translating Business Goals into Product Decisions
Explore data operations and automation in finance with Richa Sachdev. Learn to translate business goals into product decisions, optimize user experience, and leverage MLOps strategies for success.