A Simple 'Hello World' Machine Learning (ML) Example In Python

Description

This is a simple project demonstrating the most basic ML example I could find on the internet:

https://developers.google.com/codelabs/tensorflow-1-helloworld#0

There were three or four questions I wanted to answer with this example:

1. What is the simples ML example of training a model I could write?
2. Give me a simple example using TensorFlow so I can start to get familiar with it.
3. When the model is created, where does it 'live' and how might I re-use it without having to train it every time.
4. Given a simple ML example, how does it's computation compare to a programmed version of the same? This is one key question I have about ML models, especially with regard to chess, for example. How do trained chess ML models compare with the hand-crafted chess game engines? Are they better, worse, faster, slower? This example is too simple to provide an answer, but the comparison is interesting, I think.

To Train The Brain/Model

First, you'll need to install TensorFlow and Numpy:

1. pip install --upgrade pip
2. pip install tensorflow
3. pipe install numpy
4. Then run the training example: python3 train_hello_world.py
5. To re-use the model you just generated, run: python3 use_hello_world.py
6. Finally, to run a simple function to calculate the same results, run: python3 simple_func.py