Text & NLP

from fling import TextClassifier

tc = TextClassifier("reviews.csv", text_col="review", target="sentiment",
                   algorithm="logistic")
tc.train()
tc.evaluate()
predictions = tc.predict(["Great product!", "Terrible quality."])

from fling import TextVectorizer

vec = TextVectorizer(max_features=5000, ngram_range=(1, 2))
word_matrix = vec.fit_transform(df["text"])

from fling import TextSimilarity

sim = TextSimilarity()
sim.fit(df["description"])
results = sim.most_similar("wireless bluetooth headphones", top_n=5)