version-delete for apps (#534)

intel · Jul 16, 2018 · de68f9e · de68f9e
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diff --git a/apps/anomaly-detection/README.md b/apps/anomaly-detection/README.md
@@ -4,7 +4,6 @@ This is a simple example of unsupervised anomaly detection using Analytics Zoo K
 ## Environment
 * Python 2.7/3.5/3.6 (pandas 0.22.0)
 * Apache Spark 1.6.0/2.1.0 (This version needs to be same with the version you use to build Analytics Zoo)
-* Analytics Zoo 0.1.0
 
 ## Run with Jupyter
 * Download Analytics Zoo and build it.

diff --git a/apps/dogs-vs-cats/README.md b/apps/dogs-vs-cats/README.md
@@ -6,7 +6,6 @@ In this notebook, we will use a pre-trained Inception_V1 model. But we will oper
 * JDK 8
 * Apache Spark 2.x
 * Jupyter Notebook 4.1
-* Analytics Zoo 0.1.0
 
 ## Steps to run the notebook
 * Download Analytics Zoo and build it.

diff --git a/apps/image-augmentation/README.md b/apps/image-augmentation/README.md
@@ -4,7 +4,6 @@ This is a simple example of image augmentation using Analytics ZOO API. We use v
 ## Environment
 * Python 2.7/3.5/3.6 (numpy 1.11.1)
 * Apache Spark 1.6.0/2.1.0 (This version needs to be same with the version you use to build Analytics Zoo)
-* Analytics ZOO 0.1.0
 
 ## Run with Jupyter
 * Download Analytics Zoo and build it.

diff --git a/apps/image-similarity/README.md b/apps/image-similarity/README.md
@@ -6,7 +6,6 @@ provided by users.
 ## Environment
 * Python 2.7/3.5/3.6
 * Apache Spark 1.6.0/2.1.0 (This version needs to be same with the version you use to build Analytics Zoo)
-* Analytics Zoo 0.1.0
 
 ## Run with Jupyter
 * Download Analytics Zoo and build it.

diff --git a/apps/object-detection/README.md b/apps/object-detection/README.md
@@ -4,7 +4,6 @@ This is a simple example of object detection using Analytics Zoo Object Detectio
 ## Environment
 * Python 2.7/3.5/3.6 (Need moviepy)
 * Apache Spark 1.6.0/2.1.0 (This version needs to be same with the version you use to build Analytics Zoo)
-* Analytics Zoo 0.1.0
 
 ## Run with Jupyter
 * Download Analytics Zoo and build it.

diff --git a/apps/recommendation/README.md b/apps/recommendation/README.md
@@ -6,7 +6,6 @@ These two notebooks demonstrate how to build neural network recommendation syste
 * JDK 8
 * Spark 1.6.0/2.1.1/2.1.2/2.2.0(This version needs to be same with the version you use to build Analytics Zoo)
 (wide_n_deep needs to use Spark version >= 2.1.2)
-* Analytics Zoo 0.1.0
 * Jupyter Notebook 4.1
 
 ## Steps to run the notebook

diff --git a/apps/sentiment-analysis/README.md b/apps/sentiment-analysis/README.md
@@ -12,7 +12,6 @@ In this example, you will learn how to use Analytics Zoo to develop deep learnin
 ## Environment
 * Python 2.7/3.5/3.6
 * Apache Spark 1.6.0/2.1.0 (This version needs to be same with the version you use to build Analytics Zoo)
-* Analytics Zoo 0.1.0
 
 ## Run with Jupyter
 * Download Analytics Zoo and build it.

diff --git a/apps/tfnet/README.md b/apps/tfnet/README.md
@@ -5,7 +5,6 @@ This example demonstrates how to do image classification inference using a pre-t
 ## Environment
 * Tensorflow 1.8.0
 * Apache Spark 1.6.0/2.1.0 (This version needs to be same with the version you use to build Analytics Zoo)
-* Analytics Zoo 0.2.0
 
 ## Install Tensorflow-Slim image classification model library and down the checkpoint
 

diff --git a/apps/variational-autoencoder/README.md b/apps/variational-autoencoder/README.md
@@ -3,7 +3,6 @@
 This directory contains three notebooks to show you how to use
 [Variational Autoencoders](https://arxiv.org/pdf/1606.05908.pdf)
 in Analytics Zoo. These notebooks are developed on Apache Spark 2.1
-and Analytics Zoo 0.1.0.
 
 1. [Using Variational Autoencoder to Generate Digital Numbers](./using_variational_autoencoder_to_generate_digital_numbers.ipynb)
    This notebook used the [MNIST](http://yann.lecun.com/exdb/mnist/)