Practical Machine Learning with Tensorflow
We will cover the basics of Tensorflow and Machine Learning in the initial sessions and advanced topics in the latter part. After this course, the students will be able to build ML models using Tensorflow.
Implementing Data Capture for ML Observability and Drift Detection
Explore the implementation of data capture for machine learning observability and drift detection in this 24-minute conference talk by Pushkar Garg. Dive into the complexities of modern ML systems, including data pipelines and transformations across mult…
Going Beyond Two-Tier Data Architectures with DuckDB
Explore the innovative data architectures enabled by DuckDB, an in-process analytical data management system, in this 32-minute talk by Prof. Dr. Hannes Mühleisen. Discover how DuckDB's lightweight yet powerful design, available under the MIT license, al…
Reproducible Data Science Over Data Lakes
Explore reproducible data science techniques for data lakes in this 12-minute conference talk by Ciro Greco, presented at DE4AI. Delve into the challenges of achieving reproducibility in Lakehouse architectures and discover recent advancements made at Ba…
The Evolution of Lyft's ML Feature Store
Explore the evolution of Lyft's machine learning feature store in this 13-minute conference talk presented by Devon Mittow, a Staff Data Engineer with over a decade of experience in data engineering across various industries. Gain insights into how Lyft'…
Realtime Streaming for Anomaly Detection - An End-to-End Data Engineering Project
Build a real-time anomaly detection system using streaming data engineering techniques. Learn end-to-end implementation for monitoring and identifying unusual patterns in data streams.
Building Scalable ML Services for Rapid Development in Health and Wellness
Discover how to build and scale ML services for health and wellness products, reducing release time by 85% using open-source tools like DBT, AirFlow, and MLFlow.
Anomaly Detection on 5 Pillars of Data Observability with Dynatrace Davis AI
Explore Dynatrace Davis AI's anomaly detection for data observability pillars: freshness, distribution, volume, schema, and lineage. Learn automation techniques for alerting and monitoring data integrity.
From Idea to Production: AI Infrastructure for Scaling LLM Applications
Explore strategies for scaling LLM applications from beta to production, addressing challenges and building adaptable AI infrastructure for evolving models and workflows.
Building Real Time ML Pipelines with a Feature Store
Explore real-time ML pipeline construction using feature stores. Learn to optimize compute efficiency and enhance ML workflows for production environments.
Lessons Learned from DAG-Based Workflow Orchestration
Explore DAG-based workflow orchestration challenges and learn about Prefect Orion's DAG-less system for enhanced runtime flexibility and developer experience in data pipelines.
Building Real-Time ML Features with a Feature Platform
Explore challenges in deploying ML pipelines and learn how feature stores and platforms solve data problems for production ML, enabling real-time processing and scaling.
The Critical Things You Have to Build to Transform Your Company to be ML Driven
Discover key components for transforming your company into an ML-driven organization. Learn strategies for overcoming challenges in the machine learning development lifecycle and deploying models effectively.
Airflow: Where Data Engineers and ML Engineers Meet
Explore Apache Airflow's role in operational machine learning with a real-world demo and reference implementation of GenAI in production.
GraphRAG - Unleashing the Power of Knowledge Graphs with LLMs
Explore GraphRAG: AI-powered content interpretation using LLMs to create knowledge graphs from unstructured text, enabling advanced search and question-answering capabilities.
ByteDance's Platform for Reinforcement Learning from Human Feedback
Explore ByteDance's journey in building a video data processing pipeline using Ray's ecosystem for creating realistic video generation models from text instructions.
Apache Airflow Tutorials
Learn Apache Airflow fundamentals, set up environments, write pipelines, and integrate with Google Cloud services. Gain practical skills for efficient workflow automation and data pipeline management.
Google Cloud Platform Beginner Series
Comprehensive introduction to Google Cloud Platform, covering key technologies, hands-on exercises, and practical applications for beginners in cloud computing.
Building Data Pipelines with Apache Kafka and Confluent
Learn to build streaming data pipelines using Apache Kafka® and Confluent. Covers data ingestion, real-time transformation with ksqlDB, and data egress. Hands-on tutorials included for practical experience.
Kafka Tutorial - Spring Boot Microservices
Learn to integrate Apache Kafka with Spring Boot microservices, covering topics, producers, consumers, and building a RESTful API that interacts with the Kafka ecosystem.
Azure Data Factory Power Hour - Latest Updates and Demos
Exclusive Azure Data Factory updates and demos, including Power Query integration, managed virtual networks, Teams notifications, and user-assigned managed identities for enhanced data integration capabilities.