get an understanding for the importance of tokenization of a text when training a neural network for texts, for example, to do a sentiment analysis. Tokenization is the process of converting the text into numeric values, with a number representing a word or a character.
learn about embeddings, where the text tokens are mapped as vectors in a high dimensional space. With embeddings and labelled examples, these vectors can then be tuned so that words with similar meaning will have a similar direction in the vector space. This will begin the process of training a neural network to understand sentiment in text -- and you'll begin by looking at movie reviews, training a neural network on texts that are labelled 'positive' or 'negative' and determining which words in a sentence drive those meanings.
Week 1 and 2 of the course Natural Language Processing in TensorFlow
complete week 3 and week 4 of the course Natural Language Processing in TensorFlow
complete this notebook to generate text in the unique speaking style of Star Wars character Master Yoda.
decide on an evaluation metric for your project task and evaluate your baseline model
document the evaluation results of your baseline model and the used metric(s) in your project repository