Making ScratchML available to the public!

What you will see in this release:

• Implementation of some ML algorithms (note: MLP is not ready for production yet))
• Broad test coverage;
• A lot of activation functions and accuracy metrics (both for regression and classification) to use;
• Implementation of the Binary Cross Entropy and Cross Entropy functions;
• A lot of distance metrics to be used in clustering algorithms;
• Implementation of the Label Encoder and One-hot Encoding scalers;
• Implementation of the traditional Train-Test-Split data split function, alongside KFold, Stratified KFold, and Split Into Batches.