Scaling MLOps to Retrain 50k Weekly Models in Parallel Using UDFs
Discover how to scale MLOps for high-frequency retraining of 50k models weekly using Databricks, MLflow, and Pandas UDFs. Learn best practices for experiment tracking, code consistency, and handling data volatility at scale.
Introduction to Mosaic AI - Simplifying GenAI Development with Databricks
Explore Mosaic AI's tools for streamlining GenAI application development, deployment, and management. Learn best practices for efficient AI project creation on a secure Data Intelligence platform.
Comprehensive Guide to Mosaic AI - Getting GenAI Apps to Production on Databricks
Explore Mosaic AI for efficient GenAI app development on Databricks. Learn design, maintenance, and integration techniques through practical demonstrations to streamline your AI projects.
Latest Advancements in MLflow
Explore recent MLflow features, including GenAI additions, and learn how to optimize machine learning workflows with practical examples and best practices for implementation.
Insights from Building Enterprise-Grade ML Experiences at Asana
Discover key learnings from Asana's journey in developing and deploying machine learning features for millions of users, covering modeling, monitoring, scaling, and leveraging Databricks for data science solutions.
Unlock Data and AI Potential with a Fully Orchestrated Health Lakehouse
Explore how a modern healthcare data lakehouse integrates diverse data sources, leveraging AI and orchestration for improved patient care, risk management, and clinical decision support.
Building Your First GenAI App Using Databricks, MosaicML and MLRun
Learn to implement, scale, and manage GenAI applications using Databricks, MosaicAI, and MLRun. Explore MLOps best practices, CI/CD automation, and GPU optimization for enterprise-level AI deployment.
Building a Modern Marketing Team with Machine Learning and Databricks
Discover how Rogers leverages ML and Databricks to revolutionize marketing, featuring a reusable framework for data science across industries and insights on implementing key marketing models.
Building Production Quality Generative AI Applications
Explore a developer workflow for deploying high-quality AI applications, covering experimentation, feedback, and performance metrics using Databricks tools like Vector Search and MLflow.
Next-Gen Energy AI: Asset Bundles and MLOps on Repsol's Data and AI Platform
Explore Repsol's integration of MLOps in their Data & AI Cloud Platform, focusing on Databricks Asset Bundles for efficient ML model development and deployment in the energy sector.
The MLOps Platform at WGU - Solutions to Production ML with Databricks
Explore WGU's MARVIN platform, addressing MLOps challenges with Databricks. Learn about streamlined workflows, project templates, and strategies for efficient ML model deployment at scale.
Preparing for the Databricks Certified Generative AI Engineer Associate Exam
Explore Databricks' Generative AI Engineer Associate certification, covering key topics like prompt engineering, RAG, and LLM selection. Learn exam scope, preparation tips, and insights from experts.
From Uncertainty to Certainty: Strategies for Deterministic LLMOps
Explore strategies for implementing deterministic approaches in LLM operations, focusing on assessment, evaluation, and refinement to enhance reliability and stakeholder trust in AI applications.
MLOps GitHub Actions with CI/CD Pipeline Tutorial
Learn to implement MLOps with GitHub Actions, covering CI/CD pipelines, developer workflows, and unit testing for efficient machine learning project management and deployment.
Building a State-of-the-Art Open-Source Model - DBRX Development Story
Discover the journey behind DBRX, Databricks' open-source foundation model. Learn tools, methods, and insights for building high-quality LLMs, with real-world examples and best practices from the development team.
Exploring MLOps and LLMOps - Architectures and Best Practices
Dive into MLOps and LLMOps architectures, components, and best practices. Learn strategies for efficient implementation and improved model performance in this comprehensive technical session.
Mastering Software Operators for Data and AI - PostgreSQL, Apache Spark, and Kubeflow
Explore software operators for PostgreSQL, Apache Spark, and Kubeflow. Learn to simplify complex operations, streamline data processing, and navigate MLOps setups for optimal AI workload performance.
ML Scalability Challenges in Machine Learning - MLOps Coffee Session
Explore ML scalability challenges with Anyscale's Head of Engineering. Gain insights on large-scale computing, attention-based models, and the balance between big and small data in machine learning.
Multilingual Programming and Project Structure for Collaboration
Explore multilingual programming and project structures for effective collaboration. Learn to choose the right language for each problem and implement best practices in data science and MLOps.
Airflow's Limitations for MLOps - Challenges and Alternatives
Explore challenges in MLOps, data platforms, and Airflow with Stephen Bailey. Gain insights on modular job design, data classification, and practical approaches to data engineering and machine learning workflows.
Vertex AI Workshop - Training, Serving, and Pipelines
Explore hands-on Vertex AI for ML model training, serving, and pipeline creation. Learn to leverage Google Cloud's powerful tools for efficient machine learning workflows and deployments.