From ac25bb9289d907b26cd7ceaa0a345a1f141af653 Mon Sep 17 00:00:00 2001 From: Spring Operator Date: Mon, 25 Mar 2019 21:39:41 -0500 Subject: [PATCH] URL Cleanup This commit updates URLs to prefer the https protocol. Redirects are not followed to avoid accidentally expanding intentionally shortened URLs (i.e. if using a URL shortener). # HTTP URLs that Could Not Be Fixed These URLs were unable to be fixed. Please review them to see if they can be manually resolved. * [ ] http://clagnut.com/blog/348/ (200) with 2 occurrences could not be migrated: ([https](https://clagnut.com/blog/348/) result SSLHandshakeException). # Fixed URLs ## Fixed But Review Recommended These URLs were fixed, but the https status was not OK. However, the https status was the same as the http request or http redirected to an https URL, so they were migrated. Your review is recommended. * [ ] http://doc.madlib.net/v0.5/ (301) with 2 occurrences migrated to: https://madlib.apache.org/docs/v0.5/ ([https](https://doc.madlib.net/v0.5/) result SSLHandshakeException). ## Fixed Success These URLs were switched to an https URL with a 2xx status. While the status was successful, your review is still recommended. * [ ] http://archive.ics.uci.edu/ml/datasets/Auto+MPG with 2 occurrences migrated to: https://archive.ics.uci.edu/ml/datasets/Auto+MPG ([https](https://archive.ics.uci.edu/ml/datasets/Auto+MPG) result 200). * [ ] http://archive.ics.uci.edu/ml/datasets/Wine+Quality with 4 occurrences migrated to: https://archive.ics.uci.edu/ml/datasets/Wine+Quality ([https](https://archive.ics.uci.edu/ml/datasets/Wine+Quality) result 200). * [ ] http://github.com/necolas/normalize.css with 2 occurrences migrated to: https://github.com/necolas/normalize.css ([https](https://github.com/necolas/normalize.css) result 200). * [ ] http://nbviewer.ipython.org/gist/vatsan/dd88abb47c2fbd9e16bd with 2 occurrences migrated to: https://nbviewer.ipython.org/gist/vatsan/dd88abb47c2fbd9e16bd ([https](https://nbviewer.ipython.org/gist/vatsan/dd88abb47c2fbd9e16bd) result 200). * [ ] http://postgresapp.com/ with 2 occurrences migrated to: https://postgresapp.com/ ([https](https://postgresapp.com/) result 200). * [ ] http://repo.continuum.io/archive/Anaconda-1.9.0-MacOSX-x86_64.pkg with 2 occurrences migrated to: https://repo.continuum.io/archive/Anaconda-1.9.0-MacOSX-x86_64.pkg ([https](https://repo.continuum.io/archive/Anaconda-1.9.0-MacOSX-x86_64.pkg) result 200). * [ ] http://networkx.github.com/download.html with 2 occurrences migrated to: https://networkx.github.com/download.html ([https](https://networkx.github.com/download.html) result 301). # Ignored These URLs were intentionally ignored. * http://www with 1 occurrences --- index.html | 16 ++++++++-------- params.json | 2 +- stylesheets/normalize.css | 2 +- stylesheets/styles.css | 2 +- 4 files changed, 11 insertions(+), 11 deletions(-) diff --git a/index.html b/index.html index 7d2c5b2..fa33e73 100644 --- a/index.html +++ b/index.html @@ -52,7 +52,7 @@

  • SVM (regression & classification)
  • K-Means
  • LDA
    • -

    Refer MADlib User Docs for MADlib's user documentation. Please note that PyMADlib as of now is only compatible with MADlib v0.5. You can obtain MADlib v0.5 from MADlib v0.5. We might add support to more recent versions of MADlib depending on adoption rate. Please email me if you have a strong case for an upgrade.

    +

    Refer MADlib User Docs for MADlib's user documentation. Please note that PyMADlib as of now is only compatible with MADlib v0.5. You can obtain MADlib v0.5 from MADlib v0.5. We might add support to more recent versions of MADlib depending on adoption rate. Please email me if you have a strong case for an upgrade.

    Dependencies

    @@ -60,7 +60,7 @@

    1. You'll need the python extension psycopg2 to use PyMADlib.
    2. If you have matplotlib installed, you'll see Matplotlib visualizations for Linear Regression demo.
      3. -
    3. If you have installed networkx, you'll see a visualization of the k-means demo
      4. +
    4. If you have installed networkx, you'll see a visualization of the k-means demo
    5. PyROC is included in the source of this distribution with permission from its developer. You'll see a visualization of the ROC curves for Logistic Regression.

    @@ -95,7 +95,7 @@

    Build Environment Setup on Mac OS X 10.8

    vatsan-mac$ which python
@@ -106,7 +106,7 @@ 
    
 
    vatsan-mac$ ls /Library/PostgreSQL/9.2/
@@ -162,7 +162,7 @@ 
    
 
    
 Usage Tutorial
    
 
-
+
 Also visit PyMADlib IPython NB to download the IPython NB tutorial
    
 
 
    
@@ -202,9 +202,9 @@ 
    
 
    PyMADlib packages publicly available datasets from the UCI machine learning repository and other sources.
    
 
 
      
-
    1. Wine quality dataset from UCI Machine Learning repository
      2. 
-
    2. Auto MPG dataset from UCI ML repository from UCI Machine Learning repository
      3. 
-
    3. Wine quality dataset from UCI Machine Learning repository
      4. 
+
    4. Wine quality dataset from UCI Machine Learning repository
      5. 
+
    5. Auto MPG dataset from UCI ML repository from UCI Machine Learning repository
      6. 
+
    6. Wine quality dataset from UCI Machine Learning repository
      7. 
 
    7. Obama-Romney second presidential debate (2012) transcripts
      8. 
 
    
 Questions
    
diff --git a/params.json b/params.json
index 04e61c5..930d206 100644
--- a/params.json
+++ b/params.json
@@ -1 +1 @@
-{"name":"PyMADlib","tagline":"A Python wrapper for MADlib  - an open source library for scalable in-database machine learning algorithms","body":"A Python wrapper for MADlib - an open source library for scalable in-database machine learning algorithms\r\n\r\n## Algorithms\r\n\r\nPyMADlib currently has wrappers for the following algorithms in MADlib (version 0.5).\r\n\r\n1. Linear regression\r\n1. Logistic Regression\r\n1. SVM (regression & classification)\r\n1. K-Means \r\n1. LDA \r\n\r\nRefer [MADlib User Docs](http://doc.madlib.net/v0.5/ ) for MADlib's user documentation. Please note that PyMADlib as of now is only compatible with MADlib v0.5. You can obtain MADlib v0.5 from [MADlib v0.5](https://github.com/madlib/madlib/archive/v0.5.tar.gz). We might add support to more recent versions of MADlib depending on adoption rate. Please email me if you have a strong case for an upgrade.\r\n\r\n\r\n## Dependencies\r\n\r\n1. You'll need the python extension _**psycopg2**_ to use PyMADlib.\r\n1. If you have matplotlib installed, you'll see Matplotlib visualizations for Linear Regression demo.\r\n1. If you have installed [networkx](http://networkx.github.com/download.html), you'll see a visualization of the k-means demo\r\n1. [PyROC](https://github.com/marcelcaraciolo/PyROC) is included in the source of this distribution with permission from its developer. You'll see a visualization of the ROC curves for Logistic Regression.\r\n\r\n\r\n\r\n \r\n\r\n## Configurations\r\n\r\nTo configure your DB Connection parameters\r\nYou should create a file in your home directory\r\n\r\n>     ~/.pymadlib.config \r\n\r\nthat should look like so :\r\n\r\n\r\n>     [db_connection]  \r\n>     user = gpadmin  \r\n>     password = XXXXX  \r\n>     hostname = 127.0.0.1 (or the IP of your DB server)  \r\n>     port = 5432 (the port# of your DB)  \r\n>     database = vatsandb (the database you wish to connect to)  \r\n\r\n\r\n\r\n\r\n\r\n\r\n## Installation Instructions\r\n\r\nPyMADlib depends on `MADlib`, `psycopg2` and `Pandas`. It is easiest to work with PyMADlib if you have `Anaconda Python`.\r\n\r\n## Build Environment Setup on Mac OS X 10.8\r\n\r\n* Download & install [Anaconda-1.9.0-MacOSX-x86_64.pkg] (http://repo.continuum.io/archive/Anaconda-1.9.0-MacOSX-x86_64.pkg)\r\n\r\n* Open a terminal and check if you have Anaconda Python & the package manager conda\r\n\r\n>     vatsan-mac$ which python\r\n>     /Users/vatsan/anaconda/bin/python\r\n>     vatsan-mac$ which conda\r\n>     /Users/vatsan/anaconda/bin/conda \r\n\r\n* If you haven't installed PostgreSQL on your Mac already, you'll have to download & install `PostGreSQL` for Mac. This is so that we get some required libraries to compile the SQL Engine: psycopg2. The easiest way to install `PostGreSQL` on Mac is via `http://postgresapp.com/`. Once you've downloaded and installed PostGreSQL on Mac, it should typically be found under `/Library/PostgreSQL`\r\n\r\n>     vatsan-mac$ ls /Library/PostgreSQL/9.2/\r\n>     Library include pg_env.sh uninstall-postgresql.app\r\n>     bin installer scripts\r\n>     data lib share\r\n>     doc pgAdmin3.app stackbuilder.app\r\nI don't think the version of the `PostGreSQL` matters (9.1 or above is fine). \r\n\r\n* You may need to create some symlinks to `libpq` & `libssl` so that `psycopg2` is able to find it:\r\n\r\n>     vatsan-mac$ sudo ln -s /Users/vatsan/anaconda/lib/libssl.1.0.0.dylib /usr/lib\r\n>     vatsan-mac$ sudo ln -s /Users/vatsan/anaconda/lib/libcrypto.1.0.0.dylib /usr/lib\r\n\r\n* Install `Psycopg2` \r\n\r\n>     vatsan-mac$ conda install distribute\r\n>     vatsan-mac$ pip install psycopg2\r\n\r\n* Now we're ready to test if the installations of the required libraries were successful.\r\n\r\n>     vatsan-mac$ python -c 'import psycopg2'\r\nIf the above command did not error out, then installation was successful.\r\n\r\n* You may install `PyMADlib` by downloading the source (from PyPI) and then run the following\r\n\r\n>     sudo python setup.py build\r\n>     sudo python setup.py install\r\n\r\n* If you use easy_install or pip, simply run :\r\n\r\n>     sudo easy_install pymadlib\r\n\r\n\r\n## Usage Tutorial\r\n\r\nVisit [PyMADlib Tutorial](http://nbviewer.ipython.org/gist/vatsan/dd88abb47c2fbd9e16bd) for a tutorial on using PyMADlib\r\nAlso visit [PyMADlib IPython NB](https://gist.github.com/vatsan/dd88abb47c2fbd9e16bd) to download the IPython NB tutorial\r\n\r\n\r\n## Running the Demos\r\n\r\nYou may run the demo from the extracted directory of pymadlib like so :\r\n\r\n>     python example.py\r\n\r\n        \r\nIf you installed PyMADlib using instructions in the previous section, then simply run\r\n\r\n>     python -c 'from pymadlib.example import runDemos; runDemos()'\r\n\r\nRemember to close the Matplotlib windows that pop-up to continue with the rest of the demo.\r\n\r\n\r\n\r\n\r\n## Gallery\r\n\r\n![K-Means Cluster Visualization](https://lh3.googleusercontent.com/-bXz3gCrnQFo/UTu3lXFKbeI/AAAAAAAAKgI/Hpjsqzb_GTQ/w776-h714-p-o-k/kmeans_networkx_viz.png)\r\n\r\n![Scatter Plot - Linear Regression (numeric attributes only)](https://lh3.googleusercontent.com/-esbS5NTl58E/UTu3lfBqUXI/AAAAAAAAKgE/tawiqnTgYLQ/w470-h353-o-k/linear_reg_scatter_1.png)\r\n\r\n![Scatter Plot - Linear Regression (with categorical attributes)](https://lh6.googleusercontent.com/-vNTw5Q6d0pg/UTu3lVjBIzI/AAAAAAAAKgA/pbiLfGiYisw/w470-h353-o-k/linear_reg_scatter_2.png)\r\n\r\n![ROC Curve - Logistic Regression](https://lh3.googleusercontent.com/-ymBoJ7qQo-o/UTu3l9RUBvI/AAAAAAAAKgU/_Mc0jiM_Yq0/w470-h353-o-k/logistic_reg_pyroc.png)\r\n\r\n![Random graph visualization - Networkx](https://lh6.googleusercontent.com/-H-3h0bV8EDQ/UTu3lyED9YI/AAAAAAAAKgY/CcoJ2oSme2M/s353-c-o-k/random_networkx_viz.png)\r\n\r\n \r\n\r\n\r\n## Datasets packaged with this installation\r\n\r\nPyMADlib packages publicly available datasets from the UCI machine learning repository and other sources.\r\n\r\n1. [Wine quality dataset from UCI Machine Learning repository](http://archive.ics.uci.edu/ml/datasets/Wine+Quality)\r\n1. [Auto MPG dataset from UCI ML repository from UCI Machine Learning repository](http://archive.ics.uci.edu/ml/datasets/Auto+MPG)\r\n1. [Wine quality dataset from UCI Machine Learning repository](http://archive.ics.uci.edu/ml/datasets/Wine+Quality)\r\n1. Obama-Romney second presidential debate (2012) transcripts\r\n\r\n\r\n\r\n\r\n## Questions\r\n\r\n\r\n","google":"UA-39168204-1","note":"Don't delete this file! It's used internally to help with page regeneration."}
\ No newline at end of file
+{"name":"PyMADlib","tagline":"A Python wrapper for MADlib  - an open source library for scalable in-database machine learning algorithms","body":"A Python wrapper for MADlib - an open source library for scalable in-database machine learning algorithms\r\n\r\n## Algorithms\r\n\r\nPyMADlib currently has wrappers for the following algorithms in MADlib (version 0.5).\r\n\r\n1. Linear regression\r\n1. Logistic Regression\r\n1. SVM (regression & classification)\r\n1. K-Means \r\n1. LDA \r\n\r\nRefer [MADlib User Docs](https://madlib.apache.org/docs/v0.5/ ) for MADlib's user documentation. Please note that PyMADlib as of now is only compatible with MADlib v0.5. You can obtain MADlib v0.5 from [MADlib v0.5](https://github.com/madlib/madlib/archive/v0.5.tar.gz). We might add support to more recent versions of MADlib depending on adoption rate. Please email me if you have a strong case for an upgrade.\r\n\r\n\r\n## Dependencies\r\n\r\n1. You'll need the python extension _**psycopg2**_ to use PyMADlib.\r\n1. If you have matplotlib installed, you'll see Matplotlib visualizations for Linear Regression demo.\r\n1. If you have installed [networkx](https://networkx.github.com/download.html), you'll see a visualization of the k-means demo\r\n1. [PyROC](https://github.com/marcelcaraciolo/PyROC) is included in the source of this distribution with permission from its developer. You'll see a visualization of the ROC curves for Logistic Regression.\r\n\r\n\r\n\r\n \r\n\r\n## Configurations\r\n\r\nTo configure your DB Connection parameters\r\nYou should create a file in your home directory\r\n\r\n>     ~/.pymadlib.config \r\n\r\nthat should look like so :\r\n\r\n\r\n>     [db_connection]  \r\n>     user = gpadmin  \r\n>     password = XXXXX  \r\n>     hostname = 127.0.0.1 (or the IP of your DB server)  \r\n>     port = 5432 (the port# of your DB)  \r\n>     database = vatsandb (the database you wish to connect to)  \r\n\r\n\r\n\r\n\r\n\r\n\r\n## Installation Instructions\r\n\r\nPyMADlib depends on `MADlib`, `psycopg2` and `Pandas`. It is easiest to work with PyMADlib if you have `Anaconda Python`.\r\n\r\n## Build Environment Setup on Mac OS X 10.8\r\n\r\n* Download & install [Anaconda-1.9.0-MacOSX-x86_64.pkg] (https://repo.continuum.io/archive/Anaconda-1.9.0-MacOSX-x86_64.pkg)\r\n\r\n* Open a terminal and check if you have Anaconda Python & the package manager conda\r\n\r\n>     vatsan-mac$ which python\r\n>     /Users/vatsan/anaconda/bin/python\r\n>     vatsan-mac$ which conda\r\n>     /Users/vatsan/anaconda/bin/conda \r\n\r\n* If you haven't installed PostgreSQL on your Mac already, you'll have to download & install `PostGreSQL` for Mac. This is so that we get some required libraries to compile the SQL Engine: psycopg2. The easiest way to install `PostGreSQL` on Mac is via `https://postgresapp.com/`. Once you've downloaded and installed PostGreSQL on Mac, it should typically be found under `/Library/PostgreSQL`\r\n\r\n>     vatsan-mac$ ls /Library/PostgreSQL/9.2/\r\n>     Library include pg_env.sh uninstall-postgresql.app\r\n>     bin installer scripts\r\n>     data lib share\r\n>     doc pgAdmin3.app stackbuilder.app\r\nI don't think the version of the `PostGreSQL` matters (9.1 or above is fine). \r\n\r\n* You may need to create some symlinks to `libpq` & `libssl` so that `psycopg2` is able to find it:\r\n\r\n>     vatsan-mac$ sudo ln -s /Users/vatsan/anaconda/lib/libssl.1.0.0.dylib /usr/lib\r\n>     vatsan-mac$ sudo ln -s /Users/vatsan/anaconda/lib/libcrypto.1.0.0.dylib /usr/lib\r\n\r\n* Install `Psycopg2` \r\n\r\n>     vatsan-mac$ conda install distribute\r\n>     vatsan-mac$ pip install psycopg2\r\n\r\n* Now we're ready to test if the installations of the required libraries were successful.\r\n\r\n>     vatsan-mac$ python -c 'import psycopg2'\r\nIf the above command did not error out, then installation was successful.\r\n\r\n* You may install `PyMADlib` by downloading the source (from PyPI) and then run the following\r\n\r\n>     sudo python setup.py build\r\n>     sudo python setup.py install\r\n\r\n* If you use easy_install or pip, simply run :\r\n\r\n>     sudo easy_install pymadlib\r\n\r\n\r\n## Usage Tutorial\r\n\r\nVisit [PyMADlib Tutorial](https://nbviewer.ipython.org/gist/vatsan/dd88abb47c2fbd9e16bd) for a tutorial on using PyMADlib\r\nAlso visit [PyMADlib IPython NB](https://gist.github.com/vatsan/dd88abb47c2fbd9e16bd) to download the IPython NB tutorial\r\n\r\n\r\n## Running the Demos\r\n\r\nYou may run the demo from the extracted directory of pymadlib like so :\r\n\r\n>     python example.py\r\n\r\n        \r\nIf you installed PyMADlib using instructions in the previous section, then simply run\r\n\r\n>     python -c 'from pymadlib.example import runDemos; runDemos()'\r\n\r\nRemember to close the Matplotlib windows that pop-up to continue with the rest of the demo.\r\n\r\n\r\n\r\n\r\n## Gallery\r\n\r\n![K-Means Cluster Visualization](https://lh3.googleusercontent.com/-bXz3gCrnQFo/UTu3lXFKbeI/AAAAAAAAKgI/Hpjsqzb_GTQ/w776-h714-p-o-k/kmeans_networkx_viz.png)\r\n\r\n![Scatter Plot - Linear Regression (numeric attributes only)](https://lh3.googleusercontent.com/-esbS5NTl58E/UTu3lfBqUXI/AAAAAAAAKgE/tawiqnTgYLQ/w470-h353-o-k/linear_reg_scatter_1.png)\r\n\r\n![Scatter Plot - Linear Regression (with categorical attributes)](https://lh6.googleusercontent.com/-vNTw5Q6d0pg/UTu3lVjBIzI/AAAAAAAAKgA/pbiLfGiYisw/w470-h353-o-k/linear_reg_scatter_2.png)\r\n\r\n![ROC Curve - Logistic Regression](https://lh3.googleusercontent.com/-ymBoJ7qQo-o/UTu3l9RUBvI/AAAAAAAAKgU/_Mc0jiM_Yq0/w470-h353-o-k/logistic_reg_pyroc.png)\r\n\r\n![Random graph visualization - Networkx](https://lh6.googleusercontent.com/-H-3h0bV8EDQ/UTu3lyED9YI/AAAAAAAAKgY/CcoJ2oSme2M/s353-c-o-k/random_networkx_viz.png)\r\n\r\n \r\n\r\n\r\n## Datasets packaged with this installation\r\n\r\nPyMADlib packages publicly available datasets from the UCI machine learning repository and other sources.\r\n\r\n1. [Wine quality dataset from UCI Machine Learning repository](https://archive.ics.uci.edu/ml/datasets/Wine+Quality)\r\n1. [Auto MPG dataset from UCI ML repository from UCI Machine Learning repository](https://archive.ics.uci.edu/ml/datasets/Auto+MPG)\r\n1. [Wine quality dataset from UCI Machine Learning repository](https://archive.ics.uci.edu/ml/datasets/Wine+Quality)\r\n1. Obama-Romney second presidential debate (2012) transcripts\r\n\r\n\r\n\r\n\r\n## Questions\r\n\r\n\r\n","google":"UA-39168204-1","note":"Don't delete this file! It's used internally to help with page regeneration."}
\ No newline at end of file
diff --git a/stylesheets/normalize.css b/stylesheets/normalize.css
index bc2ba93..16a1351 100644
--- a/stylesheets/normalize.css
+++ b/stylesheets/normalize.css
@@ -1,4 +1,4 @@
-/* normalize.css 2012-02-07T12:37 UTC - http://github.com/necolas/normalize.css */
+/* normalize.css 2012-02-07T12:37 UTC - https://github.com/necolas/normalize.css */
 /* =============================================================================
    HTML5 display definitions
    ========================================================================== */
diff --git a/stylesheets/styles.css b/stylesheets/styles.css
index 980ee2b..86eb093 100644
--- a/stylesheets/styles.css
+++ b/stylesheets/styles.css
@@ -42,7 +42,7 @@ by Matt Graham
   font-style: normal;
 }
 
-/* normalize.css 2012-02-07T12:37 UTC - http://github.com/necolas/normalize.css */
+/* normalize.css 2012-02-07T12:37 UTC - https://github.com/necolas/normalize.css */
 /* =============================================================================
    HTML5 display definitions
    ========================================================================== */