Hopsworks' Feature Store, Petastorm and Tensorflow

preview_player
Показать описание
On Hopsworks, learn how to:
1. Create Training/Test Datasets in Petastorm and register them with the Feature Store
2. Use Petastorm Training/Test datasets in the Feature Store to train and score a model in TensorFlow
  1. Jim Dowling
  2. Petastorm
  3. feature store
  4. tensorflow
  5. hopsworks
Рекомендации по теме
Hopsworks' Feature Store, 0:15:23

Hopsworks' Feature Store, Petastorm and Tensorflow

Hopsworks Feature 0:11:55

Hopsworks Feature Store and S3

How to interact 0:00:58

How to interact with the Hopsworks Feature Store using the Java or Scala API

Hopsworks 2.0: Feature 0:01:06

Hopsworks 2.0: Feature Store with an Advanced End-to-End ML Platform

Hopsworks Feature Store 0:57:00

Hopsworks Feature Store with Microsoft Azure

Building a Feature 0:29:47

Building a Feature Store around Dataframes and Apache Spark

End-to-End ML with 0:16:10

End-to-End ML with Hopsworks' Feature Store, SKLearn, Model Serving, Inference

Jim Dowling - 0:31:41

Jim Dowling - Hopsworks.AI - A feature Store for Machine Learning | PyData Fest Amsterdam 2020

Build ML models 0:06:38

Build ML models with fastai and Jupyter in Hopsworks

End-to-end anomaly detection 0:16:54

End-to-end anomaly detection model using the Hopsworks platform

Building a Feature 0:29:46

Building a Feature Store around Dataframes and Apache Spark

Bay Area AI: 0:31:20

Bay Area AI: Jim Downing, The Feature Store: the missing API between Data Engineering Science?

Feature store On 0:09:32

Feature store On Hops: A Data Management Layer for Machine Learning. - Kim Hammar

The Feature Store 0:31:17

The Feature Store - Jim Dowling

[Uber Open Source] 0:29:31

[Uber Open Source] Petastorm: Uber ATG's Data Access Library for Deep Learning -- Yevgeni Litv...

The Architecture That 0:19:02

The Architecture That Powers Twitter's Feature Store | Brittany Wills, Twitter

Intro to MNIST 0:07:55

Intro to MNIST on Hopsworks

End-to-End ML pipelines 0:43:26

End-to-End ML pipelines with Beam, Flink, TensorFlow, and Hopsworks (Beam Summit Europe 2019)

MLOps with a 0:56:41

MLOps with a Feature Store: Filling the Gap in ML Infrastructure | Fabio Buso, Logical Clocks AB

End-to-End ML pipelines 0:39:59

End-to-End ML pipelines with Beam, Flink, TensorFlow, and Hopsworks by Theofilos Kakantousis

HopsWorks Instalĺation with 0:10:13

HopsWorks Instalĺation with karamel

Quantcast: Lessons Learned 0:02:03

Quantcast: Lessons Learned Rebuilding a Large Scale Real-time Feature Store

Hyperparam optimization on 0:13:55

Hyperparam optimization on TensorFlow with Hopsworks

Berlin Buzzwords 2019: 0:39:28

Berlin Buzzwords 2019: Jim Dowling – Hops in the Cloud #bbuzz