Skip to main content

The book is finally available on Packt!

My book "Hands-on Deep Learning with Apache Spark" is finally available on Packt. Here's the final cover:



This is the book content:
1: THE APACHE SPARK ECOSYSTEM
2: DEEP LEARNING BASICS
3: EXTRACT, TRANSFORM, LOAD
4: STREAMING
5: CONVOLUTIONAL NEURAL NETWORKS
6: RECURRENT NEURAL NETWORKS
7: TRAINING NEURAL NETWORKS WITH SPARK
8: MONITORING AND DEBUGGING NEURAL NETWORK TRAINING
9: INTERPRETING NEURAL NETWORK OUTPUT
10: DEPLOYING ON A DISTRIBUTED SYSTEM
11: NLP BASICS
12: TEXTUAL ANALYSIS AND DEEP LEARNING
13: CONVOLUTION
14: IMAGE CLASSIFICATION
15: WHAT'S NEXT FOR DEEP LEARNING?

DeepLearning4J (Scala), but also Keras and TensorFlow (Python) are the reference frameworks.
More topics on Deep Learning on the JVM and Spark would be covered in the next months in this blog.
Labels:

Comments

  1. hermanFebruary 5, 2019 at 5:58 PM

    This comment has been removed by the author.

    ReplyDelete
  2. hermanFebruary 6, 2019 at 3:51 PM

    This comment has been removed by the author.

    ReplyDelete
  3. hermanFebruary 6, 2019 at 3:56 PM

    This comment has been removed by the author.

    ReplyDelete
  4. hermanFebruary 6, 2019 at 4:06 PM

    Hi Guglielmo,
    I am trying the code in the chapter 4.
    I am not a Java or Scala developer and I'm feeling loss with the errors that I found executing the jar that I have compiled with Maven project.
    I appended to the pom.xml file the scala plugin needed for scala code build and a shaded plugin needed to solve an error about Hadoop filesystem not found .The following is the build part that I have appended


    (build)
    (plugins)
    (!-- Configure maven-compiler-plugin to use the desired Java version --)
    (plugin)
    (groupId)org.apache.maven.plugins(/groupId)
    (artifactId)maven-compiler-plugin(/artifactId)
    (version)3.8.0(/version)
    (configuration)
    (source)${java.version}(/source)
    (target)${java.version}(/target)
    (/configuration)
    (/plugin)

    (!-- Use build-helper-maven-plugin to add Scala source and test source directories --)
    (plugin)
    (groupId)org.codehaus.mojo(/groupId)
    (artifactId)build-helper-maven-plugin(/artifactId)
    (version)3.0.0(/version)
    (executions)
    (execution)
    (id)add-source(/id)
    (phase)generate-sources(/phase)
    (goals)
    (goal)add-source(/goal)
    (/goals)
    (configuration)
    (sources)
    (source)src/main/scala(/source)
    (/sources)
    (/configuration)
    (/execution)
    (execution)
    (id)add-test-source(/id)
    (phase)generate-test-sources(/phase)
    (goals)
    (goal)add-test-source(/goal)
    (/goals)
    (configuration)
    (sources)
    (source)src/test/scala(/source)
    (/sources)
    (/configuration)
    (/execution)
    (/executions)
    (/plugin)

    (!-- Use scala-maven-plugin for Scala support --)
    (plugin)
    (groupId)net.alchim31.maven(/groupId)
    (artifactId)scala-maven-plugin(/artifactId)
    (version)3.2.2(/version)
    (executions)
    (execution)
    (goals)
    (!-- Need to specify this explicitly, otherwise plugin won't be called when doing e.g. mvn compile --)
    (goal)compile(/goal)
    (goal)testCompile(/goal)
    (/goals)
    (/execution)
    (/executions)
    (/plugin)
    (plugin)
    (groupId)org.apache.maven.plugins(/groupId)
    (artifactId)maven-shade-plugin(/artifactId)
    (version)2.3(/version)
    (executions)
    (execution)
    (phase)package(/phase)
    (goals)
    (goal)shade(/goal)
    (/goals)
    (configuration)
    (transformers)
    (transformer implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/)
    (/transformers)
    (/configuration)
    (/execution)
    (/executions)
    (/plugin)
    (/plugins)
    (/build) --)



    ReplyDelete
  5. hermanFebruary 6, 2019 at 4:07 PM

    The following is the command line that I use to submit

    $SPARK_HOME/bin/spark-submit --master local --class org.googlielmo.sparkstreamingkafka.DirectKafkaDataVec --jars /data/handsonspark/Chapter04/sparkstreamingkafka/target/sparkstreamingkafka-1.0.jar /usr/apache/spark-2.2.3/jars/*

    Now I am stuck on this error :
    Exception in thread "main" scala.MatchError: [Ljava.lang.String;@4a94ee4 (of class [Ljava.lang.String;)
    at org.googlielmo.sparkstreamingkafka.DirectKafkaDataVec$.main(DirectKafkaDataVec.scala:30)
    at org.googlielmo.sparkstreamingkafka.DirectKafkaDataVec.main(DirectKafkaDataVec.scala)
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.lang.reflect.Method.invoke(Method.java:498)
    at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:775)
    at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:180)
    at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:205)
    at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:119)
    at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)

    Please help because I am stuck from 2 days and I need to go on
    Regards
    Herman

    ReplyDelete
    Replies
    1. GooglielmoFebruary 19, 2019 at 10:39 AM

      This has been solved here: https://github.com/PacktPublishing/Hands-On-Deep-Learning-with-Apache-Spark/issues/1

      Delete

Post a Comment

Popular posts from this blog

Exporting InfluxDB data to a CVS file

Sometimes you would need to export a sample of the data from an InfluxDB table to a CSV file (for example to allow a data scientist to do some offline analysis using a tool like Jupyter, Zeppelin or Spark Notebook). It is possible to perform this operation through the influx command line client. This is the general syntax: sudo /usr/bin/influx -database '<database_name>' -host '<hostname>' -username '<username>'  -password '<password>' -execute 'select_statement' -format '<format>' > <file_path>/<file_name>.csv where the format could be csv , json or column . Example: sudo /usr/bin/influx -database 'telegraf' -host 'localhost' -username 'admin'  -password '123456789' -execute 'select * from mem' -format 'csv' > /home/googlielmo/influxdb-export/mem-export.csv
6 comments
Read more

jOOQ: code generation in Eclipse

jOOQ allows code generation from a database schema through ANT tasks, Maven and shell command tools. But if you're working with Eclipse it's easier to create a new Run Configuration to perform this operation. First of all you have to write the usual XML configuration file for the code generation starting from the database: <?xml version="1.0" encoding="UTF-8" standalone="yes"?> <configuration xmlns="http://www.jooq.org/xsd/jooq-codegen-2.0.4.xsd">   <jdbc>     <driver>oracle.jdbc.driver.OracleDriver</driver>     <url>jdbc:oracle:thin:@dbhost:1700:DBSID</url>     <user>DB_FTRS</user>     <password>password</password>   </jdbc>   <generator>     <name>org.jooq.util.DefaultGenerator</name>     <database>       <name>org.jooq.util.oracle.OracleDatabase</name>     ...
Post a Comment
Read more

Using Rapids cuDF in a Colab notebook

During last Spark+AI Summit Europe 2019 I had a chance to attend a talk from Miguel Martinez  who was presenting Rapids , the new Open Source framework from NVIDIA for GPU accelerated end-to-end Data Science and Analytics. Fig. 1 - Overview of the Rapids eco-system Rapids is a suite of Open Source libraries: cuDF cuML cuGraph cuXFilter I enjoied the presentation and liked the idea of this initiative, so I wanted to start playing with the Rapids libraries in Python on Colab , starting from cuDF, but the first attempt came with an issue that I eventually solved. So in this post I am going to share how I fixed it, with the hope it would be useful to someone else running into the same blocker. I am assuming here you are already familiar with Google Colab. I am using Python 3.x as Python 2 isn't supported by Rapids. Once you have created a new notebook in Colab, you need to check if the runtime for it is set to use Python 3 and uses a GPU as hardware accelerator. You...
5 comments
Read more