Machine Learning	Details	Links
‘Tu Libro A Ciegas’ model	NLP/transfer learning to classify literary categories of books. Technologies involved: Python (Transformers, Pytorch), Google BigQuery	Github_Repo
Spanish Language model	122000+ wikipedia spanish articles to create a language model (next word prediction) that could be later used for transfer learning. Technologies involved: Python (Fastai2)	Github_Repo
Multi-label apparel images prediction	Identifying type-color combination for 5 types and 6 colors of clothing’ images using a convolutional neural network (CNN). Technologies involved: Python (Fastai)	Github_Repo
‘The Simpsons’ image classification	Identifying 42 characters of ‘The Simpsons’ using a convolutional neural network (CNN). The output is the predicted probability for each of the categories. Technologies involved: Python (Fastai)	Github_Repo
Emotions in tweets	Classifies tweets in 13 different emotions. Two models: one using a random forest and other using a Long Short Term Memory (LSTM) neural network. Technologies involved: Python (Nltk, tensorflow-keras)	Github_Repo
Sentiment analysis for movie reviews	Evaluates reviews about movies, classifying them with positive or negative polarities. Two models: one with a Support Vector Machine, other that returns the result of a voting process between Naive Bayes, Multinomial Naive Bayes and Bernoulli Naive Bayes classifiers. Technologies involved: Python (Nltk)	Github_Repo