Dojo

Dojo_logo

Dojo is a Machine Learning library for Python

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Download for Mac OSX using Homebrew

brew install python
brew install pipenv

A step by step series of examples that tell you how to get a development env running

Since we are using the Python programming language as a main language, you will need to download it. You can do so from the official Python website.
Once you have Python up and running we then need to setup our development env. For that we are using Pipenv. You will need to install it. Check out these instructions to see how is done.
Now, that you have the prerequisites the only part left is too install all the other Pyhton packages that Dojo depends on. To do run the following:
```
pipenv install --dev
```
The --dev tag is used in order Pipenv to know to install also the packages that are used in the package development process.

If you plan just to use Dojo as a Machine Learning library you can install it using pip like so:

pip install pydojoml

Coming soon...

Coming soon...

Coming soon...

NumPy - Fundamental package for scientific computing with Python
SciPy - Package that provides many user-friendly and efficient numerical routines
Matplotlib - Python 2D plotting library
progressbar - Text progress bar library for Python
terminaltables - Easily draw tables in terminal/console applications

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

For the versions available, see the tags on this repository.

See also the list of contributors who participated in this project.

This project is licensed under the MIT License - see the LICENSE file for details

Eric Jones and Travis Oliphant and Pearu Peterson and others for writing such great packages - the SciPy ecosystem.
Nilton Volpato for writing progressbar
Robpol86 for writing terminaltables

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution for PyDojoML 0.4.5
File	Size	Uploaded
PyDojoML-0.4.5.tar.gz	207.5 kB	Jan 20, 2019	Details

Table of built distributions (wheels) for PyDojoML 0.4.5
File	Interpreter	ABI	Platform	Reset
PyDojoML-0.4.5-py3-none-any.whl 232.3 kB Jan 20, 2019	Python 3	none	any	Details

Total release size: 439.8 kB

Download URL	PyDojoML-0.4.5.tar.gz
Size	207.5 kB
Tags	Source
SHA-256 checksum How to use checksums	`35583b3907a0c5b3f882ae0ff2747e26d720edf94dc334cc78623436567ad66e`
BLAKE2b-256 checksum How to use checksums	`cf84206bed622d9b5df8605308329d244c7d6c8944df0ac5cc9401917d0cb11c`
Upload date	Jan 20, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.12.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.29.1 CPython/3.7.2`

Download URL	PyDojoML-0.4.5-py3-none-any.whl
Size	232.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`7518eff1f349331d28a1edda0d8318a529d6bc5c54ced10f6e0f82fbd6d73859`
BLAKE2b-256 checksum How to use checksums	`f6e8ad5868a5f5c883f21d9cf4974823434a77c37eb35319f115fd78d86a6489`
Upload date	Jan 20, 2019
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/1.12.1 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.6.3 requests-toolbelt/0.8.0 tqdm/4.29.1 CPython/3.7.2`