[PIO-24] Update donated template links

Project: http://git-wip-us.apache.org/repos/asf/incubator-predictionio/repo
Commit: 
http://git-wip-us.apache.org/repos/asf/incubator-predictionio/commit/df568b6d
Tree: 
http://git-wip-us.apache.org/repos/asf/incubator-predictionio/tree/df568b6d
Diff: 
http://git-wip-us.apache.org/repos/asf/incubator-predictionio/diff/df568b6d

Branch: refs/heads/develop
Commit: df568b6d505812928b59a662408d90119d524173
Parents: 8d80086
Author: Donald Szeto <[email protected]>
Authored: Sat Oct 8 16:38:54 2016 -0700
Committer: Donald Szeto <[email protected]>
Committed: Sat Oct 8 16:38:54 2016 -0700

----------------------------------------------------------------------
 docs/manual/source/demo/tapster.html.md         |  2 +-
 .../source/demo/textclassification.html.md.erb  |  2 +-
 docs/manual/source/gallery/templates.yaml       | 18 +++++++--------
 .../dimensionalityreduction.html.md             | 24 ++++++++++----------
 .../quickstart/_create_engine.html.md.erb       |  2 +-
 .../classification/quickstart.html.md.erb       |  2 +-
 .../quickstart.html.md.erb                      |  2 +-
 .../quickstart.html.md.erb                      |  2 +-
 .../quickstart.html.md.erb                      |  2 +-
 .../leadscoring/quickstart.html.md.erb          |  2 +-
 .../productranking/quickstart.html.md.erb       |  2 +-
 .../recommendation/quickstart.html.md.erb       |  2 +-
 .../similarproduct/quickstart.html.md.erb       |  2 +-
 .../templates/vanilla/quickstart.html.md.erb    |  2 +-
 14 files changed, 33 insertions(+), 33 deletions(-)
----------------------------------------------------------------------


http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/demo/tapster.html.md
----------------------------------------------------------------------
diff --git a/docs/manual/source/demo/tapster.html.md 
b/docs/manual/source/demo/tapster.html.md
index bd63f8a..8593fc9 100644
--- a/docs/manual/source/demo/tapster.html.md
+++ b/docs/manual/source/demo/tapster.html.md
@@ -97,7 +97,7 @@ We are going to copy the Similar Product Template into the 
PIO directory.
 
 ```
 $ cd PredictionIO
-$ pio template get PredictionIO/template-scala-parallel-similarproduct 
tapster-episode-similar
+$ pio template get apache/incubator-predictionio-template-similar-product 
tapster-episode-similar
 ```
 
 Next we are going to update the App ID in the ‘engine.json’ file to match 
the App ID we just created.

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/demo/textclassification.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/demo/textclassification.html.md.erb 
b/docs/manual/source/demo/textclassification.html.md.erb
index d08964e..8ac5579 100644
--- a/docs/manual/source/demo/textclassification.html.md.erb
+++ b/docs/manual/source/demo/textclassification.html.md.erb
@@ -24,7 +24,7 @@ You should also download the engine template named Text 
Classification Engine
 that accompanies this tutorial by cloning the template repository:
 
 ```
-pio template get PredictionIO/template-scala-parallel-textclassification < 
Your new engine directory >
+pio template get apache/incubator-predictionio-template-text-classifier < Your 
new engine directory >
 ```
 
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/gallery/templates.yaml
----------------------------------------------------------------------
diff --git a/docs/manual/source/gallery/templates.yaml 
b/docs/manual/source/gallery/templates.yaml
index 765719e..80a69e3 100644
--- a/docs/manual/source/gallery/templates.yaml
+++ b/docs/manual/source/gallery/templates.yaml
@@ -20,7 +20,7 @@
 
 - template:
     name: E-Commerce Recommendation
-    repo: 
"https://github.com/PredictionIO/template-scala-parallel-ecommercerecommendation";
+    repo: 
"https://github.com/apache/incubator-predictionio-template-ecom-recommender";
     description: |-
       This engine template provides personalized recommendation for e-commerce 
applications with the following features by default:
 
@@ -37,7 +37,7 @@
 
 - template:
     name: E-Commerce Recommendation (Java)
-    repo: 
"https://github.com/PredictionIO/template-java-parallel-ecommercerecommendation";
+    repo: 
"https://github.com/apache/incubator-predictionio-template-java-ecom-recommender";
     description: |-
       This engine template provides personalized recommendation for e-commerce 
applications with the following features by default:
 
@@ -66,7 +66,7 @@
 
 - template:
     name: Similar Product
-    repo: 
"https://github.com/PredictionIO/template-scala-parallel-similarproduct";
+    repo: 
"https://github.com/apache/incubator-predictionio-template-similar-product";
     description: |-
        This engine template recommends products that are "similar" to the 
input product(s). Similarity is not defined by user or item attributes but by 
users' previous actions. By default, it uses 'view' action such that product A 
and B are considered similar if most users who view A also view B. The template 
can be customized to support other action types such as buy, rate, like..etc
     tags: [recommender]
@@ -102,7 +102,7 @@
 
 - template:
     name: Recommendation
-    repo: 
"https://github.com/PredictionIO/template-scala-parallel-recommendation";
+    repo: 
"https://github.com/apache/incubator-predictionio-template-recommender";
     description: |-
       An engine template is an almost-complete implementation of an engine. 
PredictionIO's Recommendation Engine Template has integrated Apache Spark 
MLlib's Collaborative Filtering algorithm by default. You can customize it 
easily to fit your specific needs.
     tags: [unsupervised]
@@ -114,7 +114,7 @@
 
 - template:
     name: Classification
-    repo: 
"https://github.com/PredictionIO/template-scala-parallel-classification";
+    repo: 
"https://github.com/apache/incubator-predictionio-template-attribute-based-classifier";
     description: |-
       An engine template is an almost-complete implementation of an engine. 
PredictionIO's Classification Engine Template has integrated Apache Spark 
MLlib's Naive Bayes algorithm by default.
     tags: [classification]
@@ -397,7 +397,7 @@
 
 - template:
     name: Text Classification
-    repo: 
"https://github.com/PredictionIO/template-scala-parallel-textclassification";
+    repo: 
"https://github.com/apache/incubator-predictionio-template-text-classifier";
     description: |-
       Use this engine for general text classification purposes. Uses OpenNLP 
library for text vectorization, includes t.f.-i.d.f.-based feature 
transformation and reduction, and uses Spark MLLib's Multinomial Naive Bayes 
implementation for classification.
     tags: [nlp]
@@ -504,10 +504,10 @@
     pio_min_version: 0.9.5
 
 - template:
-    name: Vanilla
-    repo: "https://github.com/PredictionIO/template-scala-parallel-vanilla";
+    name: Skeleton
+    repo: "https://github.com/apache/incubator-predictionio-template-skeleton";
     description: |-
-      Vanilla template is for developing new engine when you find other engine 
templates do not fit your needs. This template provides a skeleton to kick 
start new engine development.
+      Skeleton template is for developing new engine when you find other 
engine templates do not fit your needs. This template provides a skeleton to 
kick start new engine development.
     tags: [other]
     type: Parallel
     language: Scala

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/machinelearning/dimensionalityreduction.html.md
----------------------------------------------------------------------
diff --git a/docs/manual/source/machinelearning/dimensionalityreduction.html.md 
b/docs/manual/source/machinelearning/dimensionalityreduction.html.md
index 042eb19..fd26577 100644
--- a/docs/manual/source/machinelearning/dimensionalityreduction.html.md
+++ b/docs/manual/source/machinelearning/dimensionalityreduction.html.md
@@ -19,33 +19,33 @@ In machine learning, specifically in [supervised 
learning](http://en.wikipedia.o
 | ![Square Samples](/images/machinelearning/featureselection/square100.png) | 
![Cube Samples](/images/machinelearning/featureselection/cube100.png) |
 |                                                          |                   
                                   |
 
-Dimensionality reduction is the process of applying a transformation to your 
feature vectors in order to produce a vector with the same or less number of 
features. Principal component Analysis (PCA) is a technique for dimensionality 
reduction. This can be treated as a data processing technique, and so with 
respect to the [DASE](/customize/) framework, it will fall into the Data 
Preparator engine component. 
+Dimensionality reduction is the process of applying a transformation to your 
feature vectors in order to produce a vector with the same or less number of 
features. Principal component Analysis (PCA) is a technique for dimensionality 
reduction. This can be treated as a data processing technique, and so with 
respect to the [DASE](/customize/) framework, it will fall into the Data 
Preparator engine component.
 
 This guide will also help to solidify the concept of taking an engine template 
and customizing it for a particular use case: hand-written numeric digit 
recognition.
 
 ## Data Example
 
-As a guiding example, a base data set, the [MNIST digit recognition 
dataset](https://www.kaggle.com/c/digit-recognizer/data), is used. This is a 
perfect data set for dimensionality reduction, for, in this data set, the 
features that will be used for learning are pixel entries in a \\(28 \times 
28\\) pixel image. There is really no direct interpretation of any one feature, 
so that you do not lose anything in applying a transformation that will treat 
the features as [linear 
combinations](https://en.wikipedia.org/wiki/Linear_combination) of some set 
"convenient" vectors. 
+As a guiding example, a base data set, the [MNIST digit recognition 
dataset](https://www.kaggle.com/c/digit-recognizer/data), is used. This is a 
perfect data set for dimensionality reduction, for, in this data set, the 
features that will be used for learning are pixel entries in a \\(28 \times 
28\\) pixel image. There is really no direct interpretation of any one feature, 
so that you do not lose anything in applying a transformation that will treat 
the features as [linear 
combinations](https://en.wikipedia.org/wiki/Linear_combination) of some set 
"convenient" vectors.
 
 Now, we first pull the [classification engine 
template](/gallery/template-gallery/#classification) via the following bash line
 
 ```
-pio template get PredictionIO/template-scala-parallel-classification <Your new 
engine directory>
+pio template get 
apache/incubator-predictionio-template-attribute-based-classifier <Your new 
engine directory>
 ```
 
 You should immediately be prompted with the following message:
 
 ```
-Please enter the template's Scala package name (e.g. com.mycompany): 
+Please enter the template's Scala package name (e.g. com.mycompany):
 ```
 
-Go ahead and input `FeatureReduction`, and feel free to just press enter for 
the remaining message prompts. For the remainder of this guide, you will be 
working in your new engine directory, so go ahead and `cd` into your new engine 
directory. At this point, go ahead and run the command 
+Go ahead and input `FeatureReduction`, and feel free to just press enter for 
the remaining message prompts. For the remainder of this guide, you will be 
working in your new engine directory, so go ahead and `cd` into your new engine 
directory. At this point, go ahead and run the command
 
 ```
 pio build
-``` 
+```
 
-This will make sure that the PredictionIO dependency version for your project 
matches the version installed on your computer. Now, download the MNIST 
`train.csv` data set from the link above, and put this file in the `data` 
directory contained in the new engine directory. 
+This will make sure that the PredictionIO dependency version for your project 
matches the version installed on your computer. Now, download the MNIST 
`train.csv` data set from the link above, and put this file in the `data` 
directory contained in the new engine directory.
 
 ### **Optional**: Visualizing Observations
 
@@ -165,7 +165,7 @@ PCA begins with the data matrix \\(\bf X\\) whose rows are 
feature vectors corre
 
 **Input:** \\(N \times p\\) data matrix \\(\bf X\\); \\(k \leq p\\), the 
number of desired features.
 
-**1.** For each column in the data matrix: compute the average of all the 
entries contained in the column, and then subtract this average from each of 
the column entries. 
+**1.** For each column in the data matrix: compute the average of all the 
entries contained in the column, and then subtract this average from each of 
the column entries.
 
 **2.** Compute the \\(k\\) eigenvectors corresponding to the \\(k\\) largest 
eigenvalues of the matrix obtained in the first step.
 
@@ -271,7 +271,7 @@ The motivation for defining the `Observation` class is to 
make it easy to mainta
 
 ### Preparator Modifications
 
-Remember that the Data Preparator is the engine component that takes care of 
the necessary data processing prior to the fitting of a predictive model in the 
Algorithm component. Hence this stage is where you will implement PCA. 
+Remember that the Data Preparator is the engine component that takes care of 
the necessary data processing prior to the fitting of a predictive model in the 
Algorithm component. Hence this stage is where you will implement PCA.
 
 To make sure there is no confusion, replace the import statements in the 
`Preparator.scala` script with the following:
 
@@ -293,7 +293,7 @@ numFeatures : Int
 ) extends Params
 ```
 
-The next step is to implement the algorithm discussed in the above digression. 
This will all be done in the `PreparedData` class. 
+The next step is to implement the algorithm discussed in the above digression. 
This will all be done in the `PreparedData` class.
 
 Remember that the classes `Observation` and `Query` store the pixel features 
as a string separated by `", "`. Hence, for data processing, you first need a 
function, `string2Vector`, that will transform the feature strings to vectors. 
Now, you will need a function, `scaler`, that centers your observations (step 1 
in PCA algorithm). Luckily, the `StandardScaler` and `StandardScalerModel` 
classes implemented in Spark MLLib can easily take care of this for you. The 
last part will be to actually compute the SVD of the data matrix which can also 
be easily done in MLLib. All this will be implemented in the `PreparedData` 
class which you will redefine as follows:
 
@@ -353,11 +353,11 @@ The Data Preparator engine component is now complete, and 
we can move on to the
 
 ### Algorithm Modifications
 
-The default algorithm used in the classification template is Naive Bayes. Now, 
this is a [probabilistic 
classifier](https://en.wikipedia.org/wiki/Probabilistic_classification) that 
makes certain assumptions about the data that do not really match the format of 
the PCA-transformed data. In particular, it assumes that the vectors consist of 
counts. In particular, this means it assumes non-negative feature values. 
However, upon applying PCA on the data, you have no guarantees that you will 
have purely non-negative features. Given this, you will delete the script 
`NaiveBayesAlgorithm.scala`, and create one called `LRAlgorithm.scala` (in the 
`src/main/scala/` directory) which implements [Multinomial Logistic 
Regression](https://en.wikipedia.org/wiki/Multinomial_logistic_regression). 
+The default algorithm used in the classification template is Naive Bayes. Now, 
this is a [probabilistic 
classifier](https://en.wikipedia.org/wiki/Probabilistic_classification) that 
makes certain assumptions about the data that do not really match the format of 
the PCA-transformed data. In particular, it assumes that the vectors consist of 
counts. In particular, this means it assumes non-negative feature values. 
However, upon applying PCA on the data, you have no guarantees that you will 
have purely non-negative features. Given this, you will delete the script 
`NaiveBayesAlgorithm.scala`, and create one called `LRAlgorithm.scala` (in the 
`src/main/scala/` directory) which implements [Multinomial Logistic 
Regression](https://en.wikipedia.org/wiki/Multinomial_logistic_regression).
 
 The implementation details are not discussed in this guide, as the point of 
this guide is to show how to incorporate **dimensionality reduction** 
techniques by incorporating PCA. The latter paragraph is mentioned in order to 
emphasize the fact that applying the PCA transformation (or possibly other 
dimensionality reduction techniques) will largely remove the interpretability 
of features, so that model assumptions relying on such interpretations may no 
longer be satisfied. This is just something to keep in mind.
 
-The following code is taken from the [text classification engine 
template](/gallery/template-gallery/#classification) and adapted to match the 
project definitions.  Copy and paste into the new scala script, 
`LRAlgorithm.scala`: 
+The following code is taken from the [text classification engine 
template](/gallery/template-gallery/#classification) and adapted to match the 
project definitions.  Copy and paste into the new scala script, 
`LRAlgorithm.scala`:
 
 ```scala
 package FeatureReduction

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/partials/shared/quickstart/_create_engine.html.md.erb
----------------------------------------------------------------------
diff --git 
a/docs/manual/source/partials/shared/quickstart/_create_engine.html.md.erb 
b/docs/manual/source/partials/shared/quickstart/_create_engine.html.md.erb
index fd7c7dc..d17be2e 100644
--- a/docs/manual/source/partials/shared/quickstart/_create_engine.html.md.erb
+++ b/docs/manual/source/partials/shared/quickstart/_create_engine.html.md.erb
@@ -1,7 +1,7 @@
 Now let's create a new engine called *<%= engine_name %>* by downloading the 
<%= template_name %>. Go to a directory where you want to put your engine and 
run the following:
 
 ```
-$ pio template get PredictionIO/<%= template_repo %> <%= engine_name %>
+$ pio template get <%= template_repo %> <%= engine_name %>
 $ cd <%= engine_name %>
 ```
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/classification/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/templates/classification/quickstart.html.md.erb 
b/docs/manual/source/templates/classification/quickstart.html.md.erb
index fe75aca..f7554ee 100644
--- a/docs/manual/source/templates/classification/quickstart.html.md.erb
+++ b/docs/manual/source/templates/classification/quickstart.html.md.erb
@@ -43,7 +43,7 @@ WARNING: for version < v0.3.1, it is array of features values
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyClassification', template_name: 'Classification Engine Template', 
template_repo: 'template-scala-parallel-classification' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyClassification', template_name: 'Classification Engine Template', 
template_repo: 
'apache/incubator-predictionio-template-attribute-based-classifier' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/complementarypurchase/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git 
a/docs/manual/source/templates/complementarypurchase/quickstart.html.md.erb 
b/docs/manual/source/templates/complementarypurchase/quickstart.html.md.erb
index b9eb964..d1c38b7 100644
--- a/docs/manual/source/templates/complementarypurchase/quickstart.html.md.erb
+++ b/docs/manual/source/templates/complementarypurchase/quickstart.html.md.erb
@@ -33,7 +33,7 @@ NOTE: You can customize to use other event.
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyComplementaryPurchase', template_name: 'Complementary Purchase Engine 
Template', template_repo: 'template-scala-parallel-complementarypurchase' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyComplementaryPurchase', template_name: 'Complementary Purchase Engine 
Template', template_repo: 
'PredictionIO/template-scala-parallel-complementarypurchase' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git 
a/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb 
b/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb
index 57f8c46..4ce81ec 100644
--- 
a/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb
+++ 
b/docs/manual/source/templates/ecommercerecommendation/quickstart.html.md.erb
@@ -53,7 +53,7 @@ Likewise, if a blacklist is provided, the engine will exclude 
those products in
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyECommerceRecommendation', template_name: 'E-Commerce Recommendation Engine 
Template', template_repo: 'template-scala-parallel-ecommercerecommendation' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyECommerceRecommendation', template_name: 'E-Commerce Recommendation Engine 
Template', template_repo: 
'apache/incubator-predictionio-template-ecom-recommender' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/javaecommercerecommendation/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git 
a/docs/manual/source/templates/javaecommercerecommendation/quickstart.html.md.erb
 
b/docs/manual/source/templates/javaecommercerecommendation/quickstart.html.md.erb
index 9b2de9b..58d3893 100644
--- 
a/docs/manual/source/templates/javaecommercerecommendation/quickstart.html.md.erb
+++ 
b/docs/manual/source/templates/javaecommercerecommendation/quickstart.html.md.erb
@@ -53,7 +53,7 @@ Likewise, if a blacklist is provided, the engine will exclude 
those products in
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyECommerceRecommendation', template_name: 'E-Commerce Recommendation Engine 
Template', template_repo: 'template-java-parallel-ecommercerecommendation' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyECommerceRecommendation', template_name: 'E-Commerce Recommendation Engine 
Template', template_repo: 
'apache/incubator-predictionio-template-java-ecom-recommender' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/leadscoring/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/templates/leadscoring/quickstart.html.md.erb 
b/docs/manual/source/templates/leadscoring/quickstart.html.md.erb
index 8a66bbb..3b8eb7d 100644
--- a/docs/manual/source/templates/leadscoring/quickstart.html.md.erb
+++ b/docs/manual/source/templates/leadscoring/quickstart.html.md.erb
@@ -38,7 +38,7 @@ NOTE: You can customize what the "conversion" event is. It's 
"buy" item event by
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyLeadScoring', template_name: 'Lead Scoring Engine Template', template_repo: 
'template-scala-parallel-leadscoring' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyLeadScoring', template_name: 'Lead Scoring Engine Template', template_repo: 
'PredictionIO/template-scala-parallel-leadscoring' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/productranking/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/templates/productranking/quickstart.html.md.erb 
b/docs/manual/source/templates/productranking/quickstart.html.md.erb
index 1761780..33862e2 100644
--- a/docs/manual/source/templates/productranking/quickstart.html.md.erb
+++ b/docs/manual/source/templates/productranking/quickstart.html.md.erb
@@ -34,7 +34,7 @@ INFO: This template can easily be customized to consider more 
user events such a
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyProductRanking', template_name: 'Product Ranking Engine Template', 
template_repo: 'template-scala-parallel-productranking' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyProductRanking', template_name: 'Product Ranking Engine Template', 
template_repo: 'PredictionIO/template-scala-parallel-productranking' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/recommendation/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/templates/recommendation/quickstart.html.md.erb 
b/docs/manual/source/templates/recommendation/quickstart.html.md.erb
index f84e9d1..11e6292 100644
--- a/docs/manual/source/templates/recommendation/quickstart.html.md.erb
+++ b/docs/manual/source/templates/recommendation/quickstart.html.md.erb
@@ -38,7 +38,7 @@ NOTE: You can customize to use other event.
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyRecommendation', template_name: 'Recommendation Engine Template', 
template_repo: 'template-scala-parallel-recommendation' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyRecommendation', template_name: 'Recommendation Engine Template', 
template_repo: 'apache/incubator-predictionio-template-recommender' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/similarproduct/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/templates/similarproduct/quickstart.html.md.erb 
b/docs/manual/source/templates/similarproduct/quickstart.html.md.erb
index 82af17f..ed3e851 100644
--- a/docs/manual/source/templates/similarproduct/quickstart.html.md.erb
+++ b/docs/manual/source/templates/similarproduct/quickstart.html.md.erb
@@ -52,7 +52,7 @@ Likewise, if a black-list is provided, the engine will 
exclude those products in
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MySimilarProduct', template_name: 'Similar Product Engine Template', 
template_repo: 'template-scala-parallel-similarproduct' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MySimilarProduct', template_name: 'Similar Product Engine Template', 
template_repo: 'apache/incubator-predictionio-template-similar-product' } %>
 
 ## 3. Generate an App ID and Access Key
 

http://git-wip-us.apache.org/repos/asf/incubator-predictionio/blob/df568b6d/docs/manual/source/templates/vanilla/quickstart.html.md.erb
----------------------------------------------------------------------
diff --git a/docs/manual/source/templates/vanilla/quickstart.html.md.erb 
b/docs/manual/source/templates/vanilla/quickstart.html.md.erb
index 6e24038..62827c5 100644
--- a/docs/manual/source/templates/vanilla/quickstart.html.md.erb
+++ b/docs/manual/source/templates/vanilla/quickstart.html.md.erb
@@ -29,7 +29,7 @@ No special event requirement
 
 ## 2. Create a new Engine from an Engine Template
 
-<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyNewEngine', template_name: 'Vanilla Engine Template', template_repo: 
'template-scala-parallel-vanilla' } %>
+<%= partial 'shared/quickstart/create_engine', locals: { engine_name: 
'MyNewEngine', template_name: 'Vanilla Engine Template', template_repo: 
'apache/incubator-predictionio-template-skeleton' } %>
 
 ## 3. Generate an App ID and Access Key
 

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