MLOps: Databricks MLFlow y Optuna para Ajuste de Hiperparámetros - Español
Optimiza modelos de machine learning con Databricks, MLflow y Optuna. Aprende técnicas de ajuste de hiperparámetros usando XGBoost en un entorno práctico.
MLOps MLFlow: Databricks y MLFlow Hyper-Parameter Tuning en Español
Optimiza modelos de machine learning con Databricks y MLflow, utilizando Hyperopt y XGBoost para ajuste de hiperparámetros.
MLOps MLFlow: Mlflow Projects - Databricks and MLFlow Pipelines
Aprende a crear pipelines de ejecución con MLflow Projects, utilizando Databricks como repositorio de artefactos y servidor de seguimiento para registrar toda la actividad.
Protecting PII and PHI Data in Data Lakes with Column-Level Encryption
Explore column-level encryption techniques for protecting sensitive data in data lakes, including design, implementation, and key management, with a focus on securing PII/PHI information.
Scaling Security Threat Detection with Apache Spark and Databricks
Explore advanced security threat detection using Apache Spark and Databricks. Learn about innovative solutions for notebook-based testing, self-tuning alerts, automated investigations, and custom SDK development for enhanced cybersecurity.
Using Generative AI and Databricks Workloads to Manage Sensitive Data
Explore solutions for managing sensitive data using Databricks' Unity Catalog. Learn how to leverage AI and organizational capabilities to protect data throughout its lifecycle while enabling processing and operational use.
AI-Powered EDR: Streamlining Blackberry Cybersecurity with Databricks
Discover how Databricks optimized Blackberry's EDR system, improving incident detection speed, reducing query latency by 20%, and cutting costs by 30% while enhancing data management and cybersecurity capabilities.
Building a Secure and Scalable Cybersecurity Lakehouse - Rivian's Approach
Rivian's innovative cybersecurity lakehouse enables real-time, cross-team detections, automating response management. This scalable solution reduced implementation time and increased coverage, outperforming proprietary SIEM systems.
Becoming GDPR and CCPA Compliant Using Delta Live Tables
Explore solutions for implementing "Right to be Forgotten" in data lakehouses using Delta Live Tables, ensuring compliance with GDPR and CCPA privacy regulations.
Ensuring GDPR Compliance for Real-Time Data Pipelines
Strategies for GDPR compliance in real-time data pipelines using Databricks tools. Covers immediate solutions with Delta Lake's CDF and long-term plans for PII separation, offering practical privacy compliance approaches.
Photon: Accelerating SQL Queries on Databricks Lakehouse Platform
Explore Photon, a C++ component for efficient query execution in Databricks Lakehouse. Learn about its vectorized processing, compatibility with Apache Spark, and performance enhancements for data-driven decision-making.
Accelerating Data Science Initiatives with Databricks and Privacera
Explore how Databricks' SQL Analytics and Privacera's governance capabilities integrate to provide rapid, secure data access for advanced analytics while ensuring compliance with privacy regulations.
A Collaborative Data Science Development Workflow Using Kedro and MLflow
Explore a collaborative data science workflow using Kedro pipelines, MLflow tracking, and cloud-agnostic GPU containers for efficient model development, training, and production deployment.
What's New with Databricks Machine Learning
Explore Databricks' latest ML innovations, from data preparation to model deployment, in a detailed demo showcasing simplified lifecycle management and enhanced productivity features.
AI at Scale: Industrializing ML with Databricks
Learn to industrialize ML applications, accelerate model delivery, and optimize data science workflows while maintaining high governance standards using Databricks Lakehouse platform for enterprise-scale AI solutions.
Make Reliable ETL Easy on Delta Lake
Learn to simplify ETL development on Delta Lake, improving data quality and scaling operations. Discover how Databricks streamlines the ETL lifecycle for efficient data engineering and management.
Creating a Lakehouse on AWS
Learn to build a Lakehouse on AWS, combining data lake affordability with data warehouse performance. Discover integration with AWS services and real-world examples of high-performance, cost-effective analytics solutions.
MLflow Model Serving - From Training to Production
Comprehensive overview of MLflow Model Serving, covering offline and online scoring, deployment options, and integration with Databricks, with practical examples and recent features.
Designing and Implementing a Real-time Data Lake with Dynamically Changing Schema
Learn to build a robust streaming ETL pipeline that handles dynamically changing schemas and new event types without downtime, using Delta Lake and Databricks for real-time data lake implementation.
Building a Cloud Data Lake with Databricks and AWS - Best Practices and Implementation
Explore building a cloud data lake using Databricks and AWS. Learn about data lake architecture, AWS services, Delta Lake for reliability and performance, and best practices for implementation.
DBT Using Databricks and Delta
Learn to leverage Data Build Tool (DBT) with Databricks and Delta for efficient data lake management, including SQL-first approach, upsert capabilities, and Azure integration for enhanced observability.