Simple-functions-for-starting-machine-learning-with-Python
The current repository contains different notebooks, in which functions are implemented in Python from scratch, to understand the basic steps to carry out a machine learning problem.
Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
Prerequisites
You need Python 3.x to run the following code. You can have multiple Python versions (2.x and 3.x) installed on the same system without problems.
In Ubuntu, Mint and Debian you can install Python 3 like this:
sudo apt-get install python3 python3-pip
The Jupyter Notebook which can be installed through Python's package manager:
pip3 install --upgrade pip
pip3 install jupyter
For other Linux flavors, OS X and Windows:
Python is available at http://www.python.org/getit/
Jupyter Notebook at https://jupyter.readthedocs.io/en/latest/install.html
File descriptions
- The files "iris.csv" and "winequality-white.csv" which correspond to the 2 datasets used in the different notebooks.
- "Open_conversion_data.ipynb" is the first Jupyter notebook of the series, which treats of the initial operations to be done to read the data from a CSV file, modify the variable types in the different columns (features) of the dataset, as well as data re-scaling, such as normalization and standardization.
- "Split_dataset.ipynb" is the second Jupyter notebook of the series, where 2 approaches to split a dataset are implemented, to understand how the split between training and testing occur for machine learning problems.
- "Performance_assessment.ipynb" is the third Jupyter notebook of the series in which, accuracy metrics to measure machine learning algorithms performance are introduced, and implemented in a simple way.
Running the files
The notebooks can be directly opened on GitHub. An alternative way to open the notebooks, is to run the Jupyter Notebook. This can be done by executing the following command at the Terminal (Mac/Linux) or Command Prompt (Windows):
jupyter notebook
This will print some information about the notebook server in your terminal, including the URL of the web application (by default, http://localhost:8888):
$ jupyter notebook
[I 11:47:00.830 NotebookApp] Serving notebooks from local directory: C:\Users\EC-PM-3
[I 11:47:00.830 NotebookApp] The Jupyter Notebook is running at:
[I 11:47:00.830 NotebookApp] http://localhost:8888/?token=d22181d47f4826316a37161bb8c8469d77a5851bf9ab2c1f
[I 11:47:00.830 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
It will then open your default web browser to this URL.
When the notebook opens in your browser, you will see the Notebook Dashboard, which will show a list of the notebooks, files, and subdirectories in the directory where the notebook server was started. The notebook can then be chosen by navigating in the Notebook Dashboard.
For more information on how to run a specific jupyter notebook, you can go to the following link.
Contributing
Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.
Versioning
We use SemVer for versioning. For the versions available, see the tags on this repository.
Authors
- David Cicoria - Initial work - DavidCico
See also the list of contributors who participated in this project.