Managing Machine Learning Experiments with MLflow
Learn to manage ML experiments, reproduce pipelines, and deploy models using MLflow, an open-source tool for streamlining the machine learning lifecycle.
Bringing Structure Into an Unstructured World - Applying State-of-the-Art Machine Learning at Digits
Explore how Digits applies transformer models to extract structured information from unstructured financial data and deploys ML experiments in production using TensorFlow.
A Tale of A Thousand Pipelines: Building Scalable Deep Learning Pipelines for Time-Series Datasets
Discover scalable deep learning pipelines for massive time-series datasets, reducing costs by 80% while training hundreds of models efficiently.
Why an Event-Native Mindset Is Essential for Data Architecture
Embrace an Event-Native Mindset to build a responsive data architecture. Learn to model events, create an enterprise nervous system, and enable real-time action and prediction using event-driven knowledge architecture.
Revolutionizing Data Analysis: Combining LLM, RAG, and Domain Knowledge
Leverage NLP and RAG systems to extract insights from structured and unstructured data, generate actionable insights, and empower data-driven analysis without SQL.
Understanding Microsoft Fabric - Video 2
Explore Microsoft Fabric's architecture, services, and key concepts for self-service data analytics and AI, building on UI basics from the previous video.
How Databases Work: From Relational to NoSQL - A Comprehensive Overview
Explore the inner workings of diverse database technologies, demystifying their operations and understanding their fundamental principles.
Large-Scale Distributed Processing in Google Cloud - 7 Lessons
Explore large-scale distributed processing challenges in Google Cloud, learn monitoring techniques, and discover solutions for efficient big data handling through real-world examples.
Event Streaming for the Best of All Worlds
Explore event streaming's potential to revolutionize data processing and integration across diverse systems, enhancing real-time decision-making and operational efficiency.
What the Flux - How to Stop Worrying and Love Reactor
Explore reactive programming with Project Reactor, mastering concepts like Flux and Mono for efficient, non-blocking data handling in Java applications.
Integrate Hibernate with Your Elasticsearch Database
Learn to seamlessly integrate Hibernate with Elasticsearch, enhancing database performance and search capabilities in your Java applications.
OpenLineage: An Open Standard for Data Lineage
Explore OpenLineage, an open framework for data lineage metadata collection. Learn its purpose, data model, and integration with tools like Apache Airflow and Spark to enhance pipeline understanding and management.
What's New in Recent and Upcoming HBase Releases
Explore new features in HBase 3.0.0 and 2.6.0, including OpenTelemetry tracing, region replication, cloud-native support, and improved object storage. Learn about upcoming developments for enhanced cloud compatibility.
How to Help Apache Kafka Achieve Elasticity Based on Cloud-Native Technology
Discover how to enhance Apache Kafka's elasticity using cloud-native technology. Learn about stateless Kafka Broker architecture, Elastic Stream, and cost-saving strategies for cloud infrastructure.
Building Scalable and Resilient Event-Driven Applications with Apache Pulsar
Explore Apache Pulsar's capabilities for building scalable, resilient event-driven applications. Learn key concepts, best practices, and see a live demonstration of Pulsar's power in action.
Real-time AI Made Easy - Harnessing Generative AI Functions in Apache Kafka and Apache Pulsar
Harness Generative AI Functions in Apache Kafka and Pulsar for real-time AI applications. Explore Vector Search, Computing Embeddings, and Chat Completion use cases with a live demonstration.
Kafka Monitoring: What Matters - Key Metrics and Performance Indicators
Explore key metrics for monitoring Kafka at scale, focusing on lag performance. Learn to interpret indicators, create dashboards, and set up proactive alerts for effective troubleshooting.
Architecting Applications with Multiple Open-Source Big Data Technologies
Discover insights on architecting complex distributed systems using multiple open-source big data technologies. Learn from real-world examples in IoT, fintech, and more.
Whisky Clustering with Apache Projects - Groovy, Commons Math, Ignite, Spark, Wayang, Beam and Flink
Analyze top distilleries' whiskeys using K-means clustering from Apache projects to identify the perfect single-malt Scotch. Explore data analysis with Groovy, Commons Math, Ignite, Spark, Wayang, Beam, and Flink.
Analyzing Big Data in Azure Cloud Using Spark and Databricks
Explore Azure Databricks' key features and Spark scenarios through demos, gaining insights on best practices for big data analysis in the Azure cloud.
Building a Lakehouse on the Microsoft Intelligent Data Platform
Explore Lakehouse architecture on Microsoft Intelligent Data Platform. Learn Synapse Analytics, Delta format, and Spark-based engines for efficient big data processing and analytics.