Simulating the Superbowl: Real-Time ML to Predict the NFL
Explore DraftKings' real-time ML system for NFL predictions, featuring Monte Carlo simulations and ensemble models. Learn about their MLOps pipelines and how Databricks accelerates development.
GenAI-Enabled Co-Pilots for Data Management on Databricks Platform
Explore how GenAI co-pilots accelerate data modernization for enterprises, enhancing efficiency in data management and operations while maintaining value in strategic transformations.
Cultural Shift - Making Data and AI Everyone's Business Responsibly
Explore data and AI's impact, strategies for data literacy, ethical considerations, and AI integration in business operations. Learn to harness their transformative power responsibly.
Portfolio Management Using Multi-Agent Reinforcement Learning
Explore automated stock portfolio management using Deep Learning Reinforcement and innovative indicators like news sentiment scores, enhancing trading productivity and profitability.
Advanced Experiment Tracking for LLM-Powered Applications with Customized Open-Source MLFlow
Discover Intuit's use of open-source MLFlow for enhancing ML models and LLM applications through experiment tracking, reproducibility, model lineage, and streamlined review workflows.
How to Get the Most Out of Databricks Notebooks
Discover powerful features in Databricks Notebooks to enhance collaboration, boost productivity, and elevate exploratory data analysis for data and AI teams.
Building a Production Scale, Totally Private, OSS RAG Pipeline with DBRX, Spark, and LanceDB
Discover how to create a secure, scalable AI pipeline using open-source tools DBRX, Spark, and LanceDB. Learn to implement private generative AI solutions for enterprises without compromising data security or performance.
MLOps and AI Governance in Healthcare - Providence's Use Case
Providence's journey implementing MLOps and AI governance in healthcare, showcasing a robust framework for safe and equitable AI expansion, including model marketplace, deployment, and risk management.
Rewiring Your Business for AI - Strategies for Enterprise Transformation
Discover strategies for embracing AI's transformative potential in business. Learn to focus on future-oriented thinking, reimagining processes, scaling initiatives, and cultivating a visionary mindset for competitive advantage.
Introduction to Retrieval Augmented Generation (RAG) and Implementation with Databricks
Discover RAG's potential to enhance AI applications with external knowledge sources. Learn implementation steps using Databricks for more intelligent, context-aware AI solutions.
Improve Your ML Projects - Embrace Reproducibility and Production Readiness with Kedro
Learn to enhance ML project efficiency using Kedro framework, focusing on reproducibility, flexibility, and production readiness. Gain hands-on Python experience for seamless integration.
Accelerating the Operational Scale-up of GenAI - Industrializing Solutions for Business Outcomes
Discover strategies for industrializing GenAI operations, from provisioning to risk management, ensuring trusted solutions that deliver business outcomes on the Databricks platform.
Dev to DevAI - The Future of App Development with Analytics and Generative AI
Explore the intersection of real-time analytics and generative AI in app development, revolutionizing business strategies and technological innovation.
Quality Assurance and Machine Learning Model Validation
Explore key steps in machine learning model validation and quality assurance, from bias detection to data leak prevention, enhancing your MLOps process.
Vertex AI - Pipelines for Your MLOps Workflows
Explore Vertex AI Pipelines for MLOps workflows, covering experiment pipelining, infrastructure management, and practical examples of machine learning development and deployment cycles.
Serverless Machine Learning Systems with Hopsworks and Github Actions
Learn to build an operational prediction service using Python and free serverless tools. Explore feature pipelines, batch predictions, and MLOps best practices with a real-world surfing wave height prediction example.
Move Fast and Don't Break Things - How to Build a Scalable Data Platform
Explore ML Operations at scale, focusing on Hamilton for efficient model deployment. Learn practical solutions and industry comparisons for data scientists and MLEs.
Minimize Risk and Accelerate MLOps with ML Monitoring and Explainability
Discover strategies to minimize risk and accelerate MLOps through ML monitoring and explainability. Learn to efficiently monitor, troubleshoot, and document ML models for improved performance and compliance.
AI as an Engineering Discipline - Best Practices and Guidelines for Modern Development
Explore the evolution of AI from theoretical concepts to practical engineering, learning best practices and guidelines for effective implementation in modern machine learning projects.
Deploying Large Language Models on Kubernetes Environments for Intelligent Applications
Master the deployment of Large Language Models on Kubernetes, enabling intelligent applications with chatbots for documentation interaction and operational tasks like anomaly detection.
Building Reproducible ML Processes with an Open Source Stack
Discover how to build truly reproducible machine learning experiments by integrating MLFlow, Git, lakeFS, and infrastructure-as-code for consistent data, code, and environment management.