In this blog post I will show you how to install your Enviroment on your local machine and create a Neural Network for multi-class classification of images of one video game MMORPG-AI.

First you need to install anaconda at this link

in this location C:\Anaconda3 , then you, check that your terminal , recognize conda

C:\conda --version
conda 4.12.0

If says 'conda' is not recognized as an internal or external command.

You can try this: for me, I installed anaconda3 into C:\Anaconda3.

Therefore you need to add C:\Anaconda3 as well as C:\Anaconda3\Scripts\ to your path variable, e.g.

set PATH=%PATH%;C:\Anaconda3;C:\Anaconda3\Scripts\

Or simply fix with adding the Environment Variable

and edit the Path with a New , and add the C:\Anaconda3 and C:\Anaconda3\Scripts\ and C:\Anaconda3\Library\bin , this last one for the download libraries from internet.

Some times if you got the problem of HTTP 000 Connection, you can copy the files libcrypto-1_1-x64.dll libssl-1_1-x64.dll from c:\Anaconda3\Library\bin to c:\Anaconda3\DLLs.

The environments supported that I will consider is Python 3.7, Keras 2.9.0 and TensorFlow 2.9

I will create an environment called keras, but you can put the name that you like.

conda create -n keras python==3.7

If you are running anaconda for first time, you should init conda with the shell that you want to work, in this case I choose the cmd.exe

conda init cmd.exe

and then close and open the terminal

conda activate keras

You will have something like this:

Microsoft Windows [Version 10.0.19044.1706]
(c) Microsoft Corporation. All rights reserved.
C:\Users\ruslanmv>conda activate keras
(keras) C:\Users\ruslanmv>

another way to perform the same is go to your Anaconda Navigator then go Environments and create new called keras

then in your terminal type the following commands:

conda install ipykernel

python -m ipykernel install --user --name keras --display-name "Python (Keras)"

Then we install Tensorflow

pip install tensorflow==2.9.0

and Keras

pip install keras==2.9.0

If you will work with Data Science projects I suggest install additional libraries:

pip install matplotlib sklearn numpy ipywidgets scipy pandas pillow tensorboard opencv-python

or simply you can create the file requirements.txt with all the libraries that you need:

pip install -r requirements.txt

then open the Jupyter notebook with the command

jupyter notebook&

then click New and Select your Kernel called Python (Keras)

And now we are ready to start working.

What I want to predict are the keys of a gamepad of a gameplay of one videogame. For this project we will try to predict the button RX, with only three possible outcomes.

RX Left, RX zero, RX Right. I have chosen this example because is not binary classification. This is a good example to show the difference between binary classification and multi-class classification and how to modify the Neural Network in this situation.