Update non-API docs #2101
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Update non-API docs #2101
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menshikh-iv
suggested changes
Jun 22, 2018
docs/src/install.rst
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| or, alternatively:: | ||
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| pip install --upgrade gensim | ||
| easy_install -U gensim |
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easy_install no more relevant (all using pip or conda now), better to replace easy_install with conda install -c conda-forge gensim.
In other places - use pip always please
docs/src/intro.rst
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| Once these statistical patterns are found, any plain text documents can be succinctly | ||
| expressed in the new, semantic representation and queried for topical similarity | ||
| against other documents. | ||
| The algorithms in Gensim, such as **Word2Vec**, **FastText**, **Latent Semantic Analysis**, **Latent Dirichlet Allocation** and **Random Projections**, discover semantic structure of documents by examining statistical co-occurrence patterns within a corpus of training documents. These algorithms are **unsupervised**, which means no human input is necessary -- you only need a corpus of plain text documents. |
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please add links to documentation pages for each model, btw, who use RandomProjections? Maybe better to add something like TfIdfModel or Doc2Vec (but not RandomProjections)
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OK. (but random projections are pretty cool, just not as hip at the moment)
docs/src/install.rst
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| @@ -28,9 +28,6 @@ platform that supports Python 2.6+ and NumPy. Gensim depends on the following so | |||
| * `NumPy <http://www.numpy.org>`_ >= 1.3. Tested with version 1.9.0, 1.7.1, 1.7.0, 1.6.2, 1.6.1rc2, 1.5.0rc1, 1.4.0, 1.3.0, 1.3.0rc2. | |||
| * `SciPy <http://www.scipy.org>`_ >= 0.7. Tested with version 0.14.0, 0.12.0, 0.11.0, 0.10.1, 0.9.0, 0.8.0, 0.8.0b1, 0.7.1, 0.7.0. | |||
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| **Windows users** are well advised to try the `Enthought distribution <http://www.enthought.com/products/epd.php>`_, | |||
| which conveniently includes Python & NumPy & SciPy in a single bundle, and is free for academic use. | |||
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| Install Python and `easy_install` | |||
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Please remove this section
docs/src/install.rst
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| ----- | ||
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| There are also alternative routes to install: | ||
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| 1. If you have downloaded and unzipped the `tar.gz source <http://pypi.python.org/pypi/gensim>`_ | ||
| for `gensim` (or you're installing `gensim` from `github <https://github.com/piskvorky/gensim/>`_), | ||
| for Gensim (or you're installing Gensim from `Github <https://github.com/piskvorky/gensim/>`_), | ||
| you can run:: | ||
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| python setup.py install |
docs/src/install.rst
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| Testing `gensim` | ||
| ---------------- | ||
| Testing Gensim | ||
| -------------- | ||
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| To test the package, unzip the `tar.gz source <http://pypi.python.org/pypi/gensim>`_ and run:: | ||
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| python setup.py test |
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tox -e {py27,py35,py36}-{win,linux}
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tox -e <PYTHON_VERSION>-<OS_VERSION>, for example, if I want to run tests on Linux with python3.6, I should run tox -e py36-win
docs/src/install.rst
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| To test the package, unzip the `tar.gz source <http://pypi.python.org/pypi/gensim>`_ and run:: | ||
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| python setup.py test | ||
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| Gensim uses Travis CI for continuous integration: |Travis|_ | ||
| Gensim uses Travis CI for continuous integration, automatically running the full test suite on each pull request and commit: |Travis|_ |
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In addition
- Appveyour (windows) and CircleCI (documentation)
- https://github.com/MacPython/gensim-wheels (python wheels)
- https://github.com/conda-forge/gensim-feedstock (conda packages)
- https://github.com/RaRe-Technologies/gensim-data (datasets & pre-trained models)
docs/src/install.rst
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| .. |Travis| image:: https://api.travis-ci.org/piskvorky/gensim.png?branch=develop | ||
| .. _Travis: https://travis-ci.org/piskvorky/gensim | ||
| .. |Travis| image:: https://travis-ci.org/RaRe-Technologies/gensim.svg?branch=develop | ||
| .. _Travis: https://travis-ci.org/RaRe-Technologies/gensim |
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Need to add (convert to from makdown first of course)
[](https://anaconda.org/conda-forge/gensim)
[](https://pypi.python.org/pypi/gensim)
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I don't think that's really needed or relevant here.
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@piskvorky I added fixes for current files.
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menshikh-iv
approved these changes
Jun 27, 2018
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Updating ancillary docs like
About,Intro,Installetc.