Alexnet implementation in tensorflow has incomplete architecture where 2 convolution neural layers are missing. This issue is in reference to the python notebook mentioned below.

https://github.com/donnemartin/data-science-ipython-notebooks/blob/master/deep-learning/tensor-flow-examples/notebooks/3_neural_networks/alexnet.ipynb

@madAndroid was kind enough to provide instructions on how to configure Redash with Auth0/SAML on the forum: https://discuss.redash.io/t/auth0-integration/586/5.

We should port this over to the Knowledge Base (either as a section in the Authentication Options page or a dedicated one).

Issue Description

When I run the example cartpole with the default parameters, it can not converge to the max reward 200, I wonder what went wrong.

Version Information

Please indicate relevant versions, including, if relevant:

• Deeplearning4j versi

Example scripts contains some dependencies not listed for Horovod, and in some cases require datasets without explaining how to obtain them. We should provide a README file along with a set of packages (requirements.txt) for successfully running the examples.

If I were to deploy cube.js using AWS serverless architecture, is athena required?

The docs https://cube.dev/docs/deployment#serverless do not mention whether Athena is optional or required. But when reading it, I assume it is required because there are athena keys in the serverless.yml config. I'm evaluating the idea of using Postgres RDS as the sole datasource for cubejs.

how to define java8 when submit application use spark-submit

name: Bug report/Feature request/Question
about: Create a report to help us improve
title: ''
label: bug/enhancement/question
assignees: ''

Environment:

• Java version:
• Scala version:
• Spark version:
• PyTorch and Python version:
• OS and version:

Checklist:

• Did you check if your bug/feature/

The official Widgets Development Guide only contains the most basic widget types as example.

There is no functional example for a Flot chart in there right now. Or is it?

Since this is one of the most useful and probably used (at leat to me) widgets it would be very helpful to extend that docum

if I understood it corretly from README.MD, we can install like this:

$ git clone https://github.com/donnemartin/dev-setup.git && cd dev-setup
$ ./.dots bootstrap osxprep brew osx

and later when we need datastores, we run

$ cd ~/dev-setup
$ ./.dots datastores

I understand that bootstrap copies the dot files to the home directory, such as .bash_profile and .exports.
but

Page
https://docs.alluxio.io/os/user/stable/en/deploy/Running-Alluxio-On-Docker.html

Summary
Two environment variables are not documented, and have negative impact when running Alluxio purely as a local disk cache via docker containers.

• ALLUXIO_WORKER_TIEREDSTORE_LEVEL0_DIRS_PATH
• ALLUXIO_RAM_FOLDER

If neither of these environment variables is set, and the docker container i

  File "/root/miniconda3/bin/pipeline", line 11, in <module>
    sys.exit(_main())
  File "/root/miniconda3/lib/python3.7/site-packages/cli_pipeline/cli_pipeline.py", line 5734, in _main
    _fire.Fire()
  File "/root/miniconda3/lib/python3.7/site-packages/fire/core.py", line 127, in Fire
    component_trace = _Fire(component, args, context, name)
  Fil

Spark 2.3 officially support run on kubernetes. While our guide of "Run on Kubernetes" is still based on a special version of Spark 2.2, which is out of date. We need to:

1. update that document to Spark 2.3
2. release the corresponding docker images.

According to the generated build

The commands to launch are the following :

docker pull andypetrella/spark-notebook:0.7.0-scala-2.11.8-spark-2.1.1-hadoop-2.7.2-with-hive
docker run -p 9001:9001 andypetrella/spark-notebook:0.7.0-scala-2.11.8-spark-2.1.1-hadoop-2.7.2-with-hive

Using that image (and I think it i

Hello,

I was able to run python scripts in dev mode using the steps provided in documentation. but for production, I am not sure which all folders to keep and the process to follow. editing the local conf and local sh files and running the server_deploy script, I was able to generate the server jar. But still i had to manually add the python context and upload my egg file.
Can someone pleas

I have noticed a small error in the documentation around S3 configurations:
https://docs.delta.io/latest/delta-storage.html#amazon-s3

On the read part, it should be load and not save:
spark.read.format("delta").load("s3a://<your-s3-bucket>/<path>/<to>/<delta-table>")

Also, I have successfully tested Delta 0.5.0 with on-premise S3 - https://min.io
There were some quirks around the

Use this checklist to track logstash wiki and documentation

• Update https://github.com/Cyb3rWard0g/HELK/wiki/Create-Plugins-Offline-Package
• Update HELK overview picture
  • remove alien vault integration
  • update with new indexes #256
• document catch all for windows
• document indexme catch all
• some general guideline on X amount of devices and or X amo

Implement Series.reindex.

https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.Series.reindex.html

Version

com.microsoft.ml.spark:mmlspark_2.11:jar:0.18.1
spark= 2.4.3
scala=2.11.12

data (csv with header) https://gist.github.com/ttpro1995/69051647a256af912803c9a16040f43a

download data and save as csv file, put into folder /data/public/HIGGS/higgs.test.predictioncsv

val data = spark.read.option("header","true").option("inferSchema", "true").csv("/data/public/HIGGS

Problem
Some of our transformers & estimators are not thoroughly tested or not tested at all.

Solution
Use OpTransformerSpec and OpEstimatorSpec base test specs to provide tests for all existing transformers & estimators.