com.intel.analytics.zoo:analytics-zoo-bigdl_0.9.1-spark_2.3.1

A distributed analytics library for Apache Spark.

License	Apache License, Version 2.0
GroupId	com.intel.analytics.zoo
ArtifactId	analytics-zoo-bigdl_0.9.1-spark_2.3.1
Last Version	0.6.0
Release Date	Oct 15, 2019
Type	jar
Description	A distributed analytics library for Apache Spark.

Download analytics-zoo-bigdl_0.9.1-spark_2.3.1

Filename	Size
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0.pom
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0.jar	6 MB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-sources.jar	1 MB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-python-api.zip	841 KB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-javadoc.jar	5 MB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-jar-with-dependencies.jar	475 MB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-jar-with-dependencies-and-spark.jar	201 MB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-dist.zip	463 MB
analytics-zoo-bigdl_0.9.1-spark_2.3.1-0.6.0-dist-all.zip	481 MB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/com.intel.analytics.zoo/analytics-zoo-bigdl_0.9.1-spark_2.3.1/ -->
<dependency>
    <groupId>com.intel.analytics.zoo</groupId>
    <artifactId>analytics-zoo-bigdl_0.9.1-spark_2.3.1</artifactId>
    <version>0.6.0</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/com.intel.analytics.zoo/analytics-zoo-bigdl_0.9.1-spark_2.3.1/
implementation 'com.intel.analytics.zoo:analytics-zoo-bigdl_0.9.1-spark_2.3.1:0.6.0'

Gradle Kotlin

// https://jarcasting.com/artifacts/com.intel.analytics.zoo/analytics-zoo-bigdl_0.9.1-spark_2.3.1/
implementation ("com.intel.analytics.zoo:analytics-zoo-bigdl_0.9.1-spark_2.3.1:0.6.0")

Apache Buildr

'com.intel.analytics.zoo:analytics-zoo-bigdl_0.9.1-spark_2.3.1:jar:0.6.0'

Apache Ivy

<dependency org="com.intel.analytics.zoo" name="analytics-zoo-bigdl_0.9.1-spark_2.3.1" rev="0.6.0">
  <artifact name="analytics-zoo-bigdl_0.9.1-spark_2.3.1" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='com.intel.analytics.zoo', module='analytics-zoo-bigdl_0.9.1-spark_2.3.1', version='0.6.0')
)

Scala SBT

libraryDependencies += "com.intel.analytics.zoo" % "analytics-zoo-bigdl_0.9.1-spark_2.3.1" % "0.6.0"

Leiningen

[com.intel.analytics.zoo/analytics-zoo-bigdl_0.9.1-spark_2.3.1 "0.6.0"]

Dependencies

compile (6)

Group / Artifact	Type	Version
joda-time : joda-time	jar	2.9.9
com.intel.analytics.bigdl : bigdl-SPARK_2.3	jar	0.9.1
org.tensorflow : libtensorflow	jar	1.13.1
org.tensorflow : proto	jar	1.13.1
org.tensorflow : tensorflow-hadoop	jar	1.13.1
com.intel.analytics.zoo : zoo-core-dist-all	pom	0.6.0

provided (7)

Group / Artifact	Type	Version
org.scala-lang : scala-compiler	jar	2.11.8
org.scala-lang : scala-reflect	jar	2.11.8
org.scala-lang : scala-library	jar	2.11.8
org.scala-lang : scala-actors	jar	2.11.8
org.scala-lang : scalap	jar	2.11.8
org.apache.spark : spark-core_2.11	jar	2.3.1
org.apache.spark : spark-mllib_2.11	jar	2.3.1

test (2)

Group / Artifact	Type	Version
org.scalatest : scalatest_2.11	jar	2.2.4
org.reflections : reflections	jar	0.9.9-RC1

Project Modules

There are no modules declared in this project.

A unified Data Analytics and AI platform for distributed TensorFlow, Keras and PyTorch on Apache Spark/Flink & Ray

---

What is Analytics Zoo?

Analytics Zoo seamless scales TensorFlow, Keras and PyTorch to distributed big data (using Spark, Flink & Ray).

• End-to-end pipeline for applying AI models (TensorFlow, PyTorch, OpenVINO, etc.) to distributed big data

  • Write TensorFlow or PyTorch inline with Spark code for distributed training and inference.
  • Native deep learning (TensorFlow/Keras/PyTorch/BigDL) support in Spark ML Pipelines.
  • Directly run Ray programs on big data cluster through RayOnSpark.
  • Plain Java/Python APIs for (TensorFlow/PyTorch/BigDL/OpenVINO) Model Inference.

• High-level ML workflow for automating machine learning tasks

  • Cluster Serving for automatically distributed (TensorFlow/PyTorch/Caffe/OpenVINO) model inference .
  • Scalable AutoML for time series prediction.

• Built-in models for Recommendation, Time Series, Computer Vision and NLP applications.

---

Why use Analytics Zoo?

You may want to develop your AI solutions using Analytics Zoo if:

• You want to easily apply AI models (e.g., TensorFlow, Keras, PyTorch, BigDL, OpenVINO, etc.) to distributed big data.
• You want to transparently scale your AI applications from a single laptop to large clusters with "zero" code changes.
• You want to deploy your AI pipelines to existing YARN or K8S clusters WITHOUT any modifications to the clusters.
• You want to automate the process of applying machine learning (such as feature engineering, hyperparameter tuning, model selection, distributed inference, etc.).

---

How to use Analytics Zoo?

• Check out the Getting Started page for a quick overview of how to use Analytics Zoo.
• Refer to the Python, Scala and Docker guides to install Analytics Zoo.
• Visit the Document Website (mirror in China) for more information on Analytics Zoo.
• Check the Powered By & Presentations pages for real-world applications using Analytics Zoo.
• Join the Google Group (or subscribe to the Mail List) for more questions and discussions on Analytics Zoo.

Versions

Version
0.6.0 Oct 15, 2019