Scaling Data and ML with Apache Spark and Feast

Building Real-Time ML Features with Feast, Spark, Redis, and KafkaПодробнее

Spark Optimisation: Building an Efficient Lakehouse - Data Science FestivalПодробнее

Distributed Machine Learning - Scaling ML Workflows with Apache SparkПодробнее

Spark at Scale: Engineering Strategies for Data Science WorkflowsПодробнее

Scaling Machine Learning with Spark (Teaser) • Adi Polak & Holden Karau • GOTO 2023Подробнее

Scaling Machine Learning Feature Engineering in Apache Spark at FacebookПодробнее

Apache Spark in 100 SecondsПодробнее

Scaling Machine Learning with Apache SparkПодробнее

Using Feast Feature Store with Apache Spark for Self-Served Data Sharing and Analysis for StreamingПодробнее

Scaling Vector Embeddings with Spark: The New Big Data Pipeline #datapipelines #dataengineeringПодробнее

Model Monitoring at Scale with Apache Spark and VertaПодробнее

Apache Spark for Big Data ProcessingПодробнее

Tuning ML Models: Scaling, Workflows, and ArchitectureПодробнее

Partitioning Vs Bucketing in Apache Spark under 60 Seconds #inteview #questionПодробнее

Scaling Machine Learning with Spark • Adi Polak & Holden Karau • GOTO 2023Подробнее

How Apache Spark Redefines Big Data Processing at Massive ScaleПодробнее

Leveraging Apache Spark for Scalable Data Prep and Inference in Deep LearningПодробнее

The five levels of Apache Spark - Data EngineeringПодробнее

Understanding Narrow Vs Wide Transformations in Apache Spark under 60 Seconds | FAQ #interviewПодробнее

Building Machine Learning Algorithms on Apache Spark - Scaling Out and Up (William Benton)Подробнее

Deep Learning at Scale with Apache Spark and DeterminedПодробнее