MLOps in Practice: Common Challenges and Lessons Learned - Meetup 114
Explore common MLOps challenges and lessons learned from industry experts. Gain insights on best practices, tool selection, and integrating MLOps into systems with varying maturity levels.
Applying DevOps Practices in Data and ML Engineering
Explore DevOps practices in data and ML engineering. Learn to create efficient data pipelines using Versatile Data Kit. Gain insights on automating development processes and abstracting data journeys for agile, quality-focused data engineering.
Building a Production Grade Document Understanding System with LLMs
Discover how to build scalable document understanding systems using LLMs, Metaflow, and open-source tools for efficient text processing and pattern recognition in production environments.
Mission to Maturity: Deploying MLOps to Scale Machine Learning
Explore MLOps deployment for scaling machine learning at M&S, covering personalization and enterprise functions. Learn about ML maturity, testing, and monitoring for production-ready systems.
Bringing an AI System from Proof of Concept to Deployment
Learn to create production-grade AI systems: from MVP to scaling, performance tuning, and MLOps. Gain insights on hardware sizing, latency optimization, and avoiding common pitfalls.
10X Faster Machine Learning: From R&D to Production
Supercharge ML experimentation with PyTorch Lightning and DVC, and streamline production using Kubeflow. Learn to overcome challenges in complex ML model development and deployment.
Deep AutoViML for TensorFlow Models and MLOps Workflows
Explore Deep AutoViML for building powerful TensorFlow models and MLOps workflows. Learn to fast prototype data pipelines and models using TF 2.4+ and Keras preprocessing layers.
Federated Learning: Unlocking the Value of Distributed Data
Explore federated learning to leverage distributed data for robust machine learning models without centralizing sensitive information. Learn benefits, challenges, and practical applications.
Boosting LLMs: Performance, Scaling, and Structured Outputs - MLOps Mini Summit 8
Explore techniques to enhance LLM performance, scale models in production, and improve structured outputs. Learn from experts about information extraction, scaling challenges, and innovative programming approaches for better AI results.
Unpacking Three Types of Feature Stores - MLOps Podcast
Explore feature stores, vector stores, and embeddings in ML and LLMs. Learn about personalization in prompts, MLOps challenges, and innovations from Featureform's CEO Simba Khadder.
Treating Prompt Engineering More Like Code - Promptimize and Test-Driven Development for AI
Explore scientific prompt evaluation with Promptimize. Learn about open-sourcing, test suites, and AI challenges. Gain insights on prompt optimization, deterministic evaluation, and the evolving landscape of AI prompt engineering.
The Next Million AI Apps - Developing Custom Models for Specialized Tasks
Develop custom AI models using fine-tuning and data-driven techniques to create differentiated products solving previously unattainable problems.
Adventures in Building CLIP and Other Large Language Models
Explore insights on building CLIP and large language models, AI integration, and balancing tech career with family life. Gain valuable perspectives from a seasoned Deep Learning Engineer.
The Centralization of Power in AI - MLOps Podcast Episode 181
Explore AI power centralization, language limitations, and open-source initiatives. Gain insights on AI transparency, accountability, and the evolving landscape of machine learning frameworks.
Designing for Forward Compatibility in Gen AI - MLOps Podcast
Explore forward compatibility in Gen AI, LLM deployment challenges, and practical solutions for securing and monitoring AI systems in production environments.
Building Defensible AI Apps - MLOps Podcast #191
Explore AI app development strategies, challenges, and opportunities with Gregory Kamradt. Gain insights on AI implementation, business process transformation, and the evolving landscape of AI technologies and applications.
The Role of Infrastructure in ML Leveraging Open Source - MLOps Podcast #197
Explore ML infrastructure's role in leveraging open-source tools. Learn about unifying data processing, experiment tracking, and monitoring in a single platform for efficient ML lifecycle management.
Language, Graphs, and AI in Industry
Explore key insights on successful ML production, focusing on ROI, common practices, and essential considerations. Gain valuable perspectives beyond typical AI news coverage.
Pioneering AI Models for Regional Languages - MLOps Podcast
Explore AI models for regional languages with Aleksa Gordić, focusing on YugoGPT for Balkan dialects. Gain insights on multilingual AI development, challenges, and opportunities in the evolving field of machine learning and MLOps.
The Myth of AI Breakthroughs - Cutting Through Hype in Neural Network Research
Explore AI realities, efficient model training, and cutting-edge research with Jonathan Frankle. Gain insights on facial recognition, the lottery ticket hypothesis, and navigating AI hype.
Data Governance and AI - Challenges and Opportunities in MLOps
Explore data governance, AI challenges, and MLOps with Alexandra Diem. Gain insights on balancing tech projects, agile methods, and integrating AI into workflows. Learn about specialized chatbots and data-driven problem-solving.