Python Deep Learning Projects

Preparing the text corpus

We will use the previously trained Natural Language Toolkit (NLTK) tokenizer (http://www.nltk.org/index.html) and stop words for the English language to clean our corpus and extract relevant unique words from the corpus. We will also create a small module to clean the provided collection, with a list of unprocessed sentences, to output the list of words:

"""**Download NLTK tokenizer models (only the first time)**"""nltk.download("punkt")nltk.download("stopwords")def sentence_to_wordlist(raw):    clean = re.sub("[^a-zA-Z]"," ", raw)    words = clean.split()    return map(lambda x:x.lower(),words)

Since we haven't yet captured the data from the text responses in our hypothetical business use case, let's collect a good quality ...