ML4T Software Installation - Revision history

Tucker: /* Warning */

2018-06-01T01:33:42Z

Warning

Bhrolenok3: /* Draft */

2018-01-09T22:20:39Z

Draft

Bhrolenok3: /* Draft */

2018-01-09T22:20:09Z

Draft

Bhrolenok3 at 23:10, 22 August 2017

2017-08-22T23:10:08Z

Bhrolenok3: /* Overview */

2017-08-22T23:04:53Z

Overview

Bhrolenok3 at 22:23, 18 August 2017

2017-08-18T22:23:27Z

Bhrolenok3: /* Overview */

2017-08-18T22:23:02Z

Overview

Bhrolenok3 at 21:35, 17 August 2017

2017-08-17T21:35:47Z

Bhrolenok3 at 18:18, 17 August 2017

2017-08-17T18:18:29Z

Tucker: /* Data */

2016-08-25T14:58:42Z

Data

← Older revision		Revision as of 01:33, 1 June 2018
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−	~~== Warning ==~~
−	This page was first written for an older version of the class (before Fall 2017). The instructions should still be useful, but be sure to check that everything is consistent with [[ML4T Software Setup]].
−
	==Attention==		==Attention==

← Older revision		Revision as of 22:20, 9 January 2018
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−	== ~~Draft~~ ==	+	== Warning ==
	This page was first written for an older version of the class (before Fall 2017). The instructions should still be useful, but be sure to check that everything is consistent with [[ML4T Software Setup]].		This page was first written for an older version of the class (before Fall 2017). The instructions should still be useful, but be sure to check that everything is consistent with [[ML4T Software Setup]].

@@ Line 1: / Line 1: @@
 == Draft ==
-This page is being updated for the Fall 2017 semester, and is currently in draft mode. This notice will be removed once this page has been finalized.
+This page was first written for an older version of the class (before Fall 2017). The instructions should still be useful, but be sure to check that everything is consistent with [[ML4T Software Setup]].
 ==Attention==

@@ Line 12: / Line 12: @@
 * We use a specific, static dataset for this course, which we will provide. If you download your own data from Yahoo (or elsewhere), you will get wrong answers on assignments.
 * While these instructions should work for either Windows, macOS, or Linux, we '''strongly recommend''' developing on recent versions of Ubuntu LTS, as there may be significant differences on Windows. You can easily create an Ubuntu based virtual machine image to develop on using any freely available VM software (VirtualBox is probably the easiest and cheapest).
-* Regardless of your OS and install method, you should still ensure that your code runs on the provided servers. If your code works on your machine, but fails on the grading machine, you will not get credit for that assignment, '''no exceptions'''.
+* Regardless of your OS and install method, you should still ensure that your code runs on the provided servers. If your code fails to run on the servers, "it works on my machine" is not a valid excuse, and '''you will receive no credit'''.
 The assignments in this class are in Python (version 2.7), and rely heavily on a few important libraries. These libraries are under active development, which unfortunately means there can be some compatibility issues between versions. This isn't an issue if you use the provided servers, but if you want to work from your local machine it is very important to make sure you have exactly the same library versions. To that end, here is a list of each library and its version number, provided in the pip freeze format:
@@ Line 42: / Line 41: @@
 * [https://virtualenv.pypa.io/en/stable/userguide/#usage virtualenv]
 * [https://pip.pypa.io/en/stable/ pip]
 == Optional software ==
@@ Line 48: / Line 46: @@
 * IPython [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
 * A Python IDE, such as [https://www.jetbrains.com/pycharm/ PyCharm] or [https://pythonhosted.org/spyder/ Spyder]

@@ Line 7: / Line 7: @@
 ==Overview==
 The assignments in this class are in Python (version 2.7), and rely heavily on a few important libraries. These libraries are under active development, which unfortunately means there can be some compatibility issues between versions. This isn't an issue if you use the provided servers, but if you want to work from your local machine it is very important to make sure you have exactly the same library versions. To that end, here is a list of each library and its version number, provided in the pip freeze format:
@@ Line 24: / Line 31: @@
    subprocess32==3.2.7
-If you are familiar with <code>pip</code> and <code>virtualenv</code> you can use this to create a virtualenv for this class which matches those version numbers. If not, this script should accomplish the same thing: [[File:ml4t-setup.py]]. The script will install <code>virtualenv</code> using <code>pip</code>, create a virtual environment in the current directory named <tt>ml4t-venv</tt>, and use <code>pip</code> to install the library versions listed above into that virtual environment. It requires [https://pypi.python.org/pypi/pip pip] which is provided by default on both macOS and Ubuntu, and comes packaged with the standard Python install for Windows. Certain backends for matplotlib may require additional libraries be installed in a platform specific way (on Ubuntu, <code>sudo apt install python-tk</code> should do the trick). You can read the documentation for <code>pip</code> and <code>virtualenv</code> here:
+If you are familiar with <code>pip</code> and <code>virtualenv</code> you can use this to create a virtualenv for this class which matches those version numbers. Here is an outline:
 * [https://virtualenv.pypa.io/en/stable/userguide/#usage virtualenv]
 * [https://pip.pypa.io/en/stable/ pip]
+* [https://www.virtualbox.org/ VirtualBox]
 == Optional software ==

@@ Line 24: / Line 24: @@
    subprocess32==3.2.7
-If you are familiar with <code>pip</code> and <code>virtualenv</code> you can use this to create a virtualenv for this class which matches those version numbers. If not, this script should accomplish the same thing: [[File:ml4t-setup.py]]. This script requires [https://pypi.python.org/pypi/pip pip] which is provided by default on both macOS and Ubuntu, and comes packaged with the standard Python install for Windows. Certain backends for <code>matplotlib</code> may require additional libraries be installed in a platform specific way.
+If you are familiar with <code>pip</code> and <code>virtualenv</code> you can use this to create a virtualenv for this class which matches those version numbers. If not, this script should accomplish the same thing: [[File:ml4t-setup.py]]. The script will install <code>virtualenv</code> using <code>pip</code>, create a virtual environment in the current directory named <tt>ml4t-venv</tt>, and use <code>pip</code> to install the library versions listed above into that virtual environment. It requires [https://pypi.python.org/pypi/pip pip] which is provided by default on both macOS and Ubuntu, and comes packaged with the standard Python install for Windows. Certain backends for matplotlib may require additional libraries be installed in a platform specific way(on Ubuntu, <code>sudo apt install python-tk</code> should do the trick). You can read the documentation for <code>pip</code> and <code>virtualenv</code> here:
 '''Important note''': We use a specific, static dataset for this course, which we will provide. If you download your own data from Yahoo (or elsewhere), you will get wrong answers on assignments.

@@ Line 4: / Line 4: @@
 ==Attention==
-The information on this page is for those who are interested to have a Python development environment on their own machine.  Keep in mind that even if you set up your own environment, your code still must run correctly on the GT servers.  Please see [[ML4T_Software_Setup]] for information on how to use those servers, and how to check out the code scaffolding for the projects.
+The information on this page is for those who are interested to have a Python development environment on their own machine.  Keep in mind that even if you set up your own environment, your code still MUST run correctly on the GT servers, so it is very important that you ensure that you have access to them.  Please see [[ML4T_Software_Setup]] for information on how to use those servers, and how to check out the code scaffolding for the projects.
 ==Overview==
-There are two main environments available to you to develop and test your code for this class:
+The assignments in this class are in Python (version 2.7), and rely heavily on a few important libraries. These libraries are under active development, which unfortunately means there can be some compatibility issues between versions. This isn't an issue if you use the provided servers, but if you want to work from your local machine it is very important to make sure you have exactly the same library versions. To that end, here is a list of each library and its version number, provided in the pip freeze format:
-# An Ubuntu Linux image we have created that you can run in a VM on your machine
+  cycler==0.10.0
-# One of several high performance machines at Georgia Tech
+  functools32==3.2.3.post2
-Both of these have been set up with the same, correct software libraries.  Your code MUST run properly in one of these environments, otherwise it may not run correctly in our auto grader.  If your code fails to run in the auto grader environment, you might not get credit for the assignment.  So it is very important that you ensure that you have access to one of these environments.
+If you are familiar with <code>pip</code> and <code>virtualenv</code> you can use this to create a virtualenv for this class which matches those version numbers. If not, this script should accomplish the same thing: [[File:ml4t-setup.py]]. This script requires [https://pypi.python.org/pypi/pip pip] which is provided by default on both macOS and Ubuntu, and comes packaged with the standard Python install for Windows. Certain backends for <code>matplotlib</code> may require additional libraries be installed in a platform specific way.
 '''Important note''': We use a specific, static dataset for this course, which we will provide. If you download your own data from Yahoo (or elsewhere), you will get wrong answers on assignments.
 == Optional software ==
@@ Line 29: / Line 32: @@
 * IPython [[http://docs.python-guide.org/en/latest/scenarios/scientific/ link]]
 * A Python IDE, such as [https://www.jetbrains.com/pycharm/ PyCharm] or [https://pythonhosted.org/spyder/ Spyder]

← Older revision		Revision as of 18:18, 17 August 2017
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		+	== Draft ==
		+	This page is being updated for the Fall 2017 semester, and is currently in draft mode. This notice will be removed once this page has been finalized.
		+
	==Attention==		==Attention==

@@ Line 29: / Line 29: @@
 == Data ==
-* Download: [https://dl.dropboxusercontent.com/u/299169754/ml4t.zip ml4t.zip] (md5 e20b1e56591b6199ef08e5e106a59780)<br/>Note: If you downloaded this prior to Aug 21, 2015, please download again. Some missing files have been included and minor issues fixed.
+It is no longer necessary to separately download and install the data.  It is provided as part of the github repository.
 == Test installation ==