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.
Learning Resources
Week 1 and 2 of the course
Until next week you should...
watch [6 Min]
watch [5 Min]
watch [8 Min]
complete to generate text in the unique speaking style of Star Wars character Master Yoda.
watch the videos "", "", and "" to help you evaluating and improving your model
consider a baseline model or a baseline comparison for your project task according to the instructions given
document the evaluation results of your baseline model and the used metric(s) in your project repository