Machine Learning

On the current Jupyter Notebook it will be done a very quick presentation of Orange.

Imagine creating a game that using the signals from your hand can try to guess what is the gesture you are making and play "Rock, Paper or Scissor" game.

After the presentation of data acquisition conditions on the previous Jupyter Notebook , we will follow our Machine Learning Journey by specifying which features will be extracted.

A diversified set of features were extracted in Rock, Paper or Scissor Game - Train and Classify [Volume 3]. However, to avoid redundancies, it is essential to ensure a careful feature selection to guarantee the training of an effective classifier. Are you ready?

After the previous two volumes of the Jupyter Notebook dedicated to our "Classification Game", we are reaching a decisive stage: Training of Classifier.