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NLP

NLP

Notebook Cell
# term freq = freq of term 't' in doc 'd' / total terms in 'd'

def tf(doc):
    temp_list = doc.split(" ") # split terms
    final_dict = {} # store final dictionary with term freq
    for i in temp_list:
        if i not in final_dict.keys(): # check if term is already present in dict
            final_dict[i] = round(temp_list.count(i)/len(temp_list),2) # calculating tf
    return final_dict

tf("I have a nice car with a nice tires")
{'I': 0.11, 'have': 0.11, 'a': 0.22, 'nice': 0.22, 'car': 0.11, 'with': 0.11, 'tires': 0.11}