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Welcome to the Machine-Learning-with-Python wiki!

This wiki accompanies the exercises in this repo and is based on the book "Introduction to Machine Learning with Python: A guide for data scientists".

Setting up the environment

To set up your computer with the necessary requirements for these exercises you will require the following:

1. A copy of Python on your machine (this repo was created using Python v3.6)
2. The following Python libraries
   • scikit-learn : A learning tool for machine learning containing versions of different machine learning algorithms
   • NumPy: A high-level mathematical library containing functionality for multidimensional arrays.
   • matplotlib: Python plotting library.
   • pandas: Python library for data wrangling 🐄 🤠 and analysis. Simply put it is able to present data nicely
   • mglearn: A library included as part of the Introduction to Machine Learning with Python book. It is a utility function to remove complexity of graphing.

Installing Python

If you navigate to this link you will be able to download the latest version of Python.

Once downloaded you will need to run the installer (make sure you run it in administrator mode if in windows).

To verify that Python has successfully installed open command prompt and enter py (if using windows) or open a terminal and enter python3 (MacOS). From this window if you type print('Hello World') you should get a line displaying that text.

Installing Python Packages

Now that python is installed we need to install the packages.

Windows:

Open a new command prompt and run the following command:

py -m pip install requests

Where requests is the name of the desired package/library. Run this command for all of the libraries mentioned above

Mac:

Open a new terminal program and run the following command:

pip3 install requests

Where requests is the name of the desired package/library. Run this command for all of the libraries mentioned above

Congratulations you have successfully set up your python environment 👏 👏 👏