Support for emojis

Performance, performance, performance

• Actions
• Japanese
• Update dependencies
• Tweek hyperparameters for best performance

The version 3 comes with some important changes, mainly focused on improve performance:

• NlpClassifier no longer exists, in favor of NluManager as the manager of several NLU classes, and is able to manage several languages and several domains inside each language.
• Now by default, each domain of a language has it's own neural network classifier. When a language has more than 1 domain, a master neural network is trained that instead of classifying into the intent, classify into de domain. That way the models are faster to train and have a better score.
• The language guesser is now trained with the trigrams from the utterances used to train. That means that has a best guessing, and also that non-existing languages are guessed (example, klingon).
• Added Tagalog and Galician languages.
• The console-bot example training time in version 2.x in my laptop was 108 seconds, in the version 3.x the training time went down to 3 seconds, so the improvement in performance is notable.
• Also the size of the model.nlp files is decreased, the console-bot example went from 1614KB down to 928KB.
• The browser version has decreased from 5.08MB down to 2.3MB

• When using LRC and Neural, give some different ways to calculate the score, by default average.