Universal Machine Learning with Apache Beam - Maximilian Michels & Robert Bradshaw

preview_player
Показать описание
Flink Forward Berlin, September 2018 #flinkforward

Apache Beam is a unified batch and streaming programming model. Apache Beam runs on various execution backends, such as Apache Flink, Apache Spark, Apache Samza, Apache Gearpump, Apache Hadoop, and Google Cloud Dataflow.

Up until recently, Java was the predominant language for writing Beam Jobs. However, thanks to the Beam portability project you can now write your pipelines in other languages (Java/Scala/Python/Go/SQL). The benefit of this is simple - Not only can you use your favorite programming language to write data processing pipelines but also all of its libraries.

After a brief introduction to Apache Beam, we want to explain how cross-language portability was made possible. Further, we want to showcase the portability with TFX, a Python library for machine learning with TensorFlow.

This talk is for everyone who wants to learn about Apache Beam, its API, and its portability layer. No machine learning knowledge required.

  1. Flink Forward
  2. flink forward
  3. apache flink
  4. data artisans
  5. stream processing
  6. big data
Рекомендации по теме
Universal Machine Learning 0:22:32

Universal Machine Learning with Apache Beam - Maximilian Michels & Robert Bradshaw

Machine Learning with 0:17:59

Machine Learning with Apache Beam

Using Apache Spark 0:27:51

Using Apache Spark for Predicting Degrading and Failing Parts in Aviation

Using Apache MXNet 0:13:40

Using Apache MXNet in Production Deep Learning Streaming Pipelines

Machine Learning with 0:36:07

Machine Learning with Apache Beam - Danny McCormick, Google - Open Source 101

Machine Learning and 0:03:08

Machine Learning and Apache Edgent with STM32F401 to Firebase

Introduction to Apache 0:41:04

Introduction to Apache PredictionIO

A Predictive Analytics 0:29:43

A Predictive Analytics Workflow on DICOM Images using Apache Spark

Introduction to Machine 0:49:31

Introduction to Machine Learning with Apache Spark and Redis - Part 1 - Spark Basics

Apache Spark St&alone 0:03:45

Apache Spark St&alone On vSphere Machine Learning Test Run | vSphere

Implementing Enterprise Apache 0:43:45

Implementing Enterprise Apache Kafka platform to enable Machine Learning | Beyond Prediction Series

Koalas: Making an 0:38:42

Koalas: Making an Easy Transition from Pandas to Apache Spark -Tim Hunter & Takuya Ueshin

Word Embeddings with 1:33:34

Word Embeddings with Python and Apache Spark 🐍

Introduction to Machine 0:32:00

Introduction to Machine Learning with Apache Spark and Redis - Part 2 - Exploratory Data Analysis

Apache Beam for 0:41:52

Apache Beam for Production Machine Learning: TensorFlow Extended (Beam Summit Europe 2019)

Apache Beam for 0:23:52

Apache Beam for Production Machine Learning: TensorFlow Extended (TFX)

Beam Summit 2021 0:20:45

Beam Summit 2021 - Scalable Predictions of Deep Learning models with Apache Beam

Apache Prediction.IO and 0:30:31

Apache Prediction.IO and Einstein

Apache Liminal (Incubating)—Orchestrate 0:27:24

Apache Liminal (Incubating)—Orchestrate the Machine Learning Pipeline

Apache Spark NLP 0:36:42

Apache Spark NLP for Healthcare: Lessons Learned Building Real-World Healthcare AI Systems

Sandy Ryza, Cloudera 0:25:07

Sandy Ryza, Cloudera - MLlib and Apache Spark

GPU Computing With 0:17:35

GPU Computing With Apache Spark And Python

Connect and Configure 0:17:04

Connect and Configure Apache ArtemisMQ with SQL Server Database

Building an open-source 0:30:53

Building an open-source ML feature store with Apache Flink