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Feature Engineering | Natural Language Processing with Python and NLTK
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Classroom Contents
NLP in Python - Natural Language Processing
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- 1 Introduction to NLP | Natural Language Processing with Python and NLTK
- 2 NLTK - Introduction | Natural Language Processing with Python and NLTK
- 3 Structured vs Unstructured data | Natural Language Processing with Python and NLTK
- 4 Reading Text Data | Natural Language Processing with Python and NLTK
- 5 Exploring the data | Natural Language Processing with Python and NLTK
- 6 NLP Pipeline for Text data | Natural Language Processing with Python and NLTK
- 7 Removing Punctuation | Pre-processing | Natural Language Processing with Python and NLTK
- 8 Tokenization | Natural Language Processing with Python and NLTK
- 9 Removing stop words | Natural Language Processing with Python and NLTK
- 10 Stemming | Natural Language Processing with Python and NLTK
- 11 Porter Stemmer in Python | Natural Language Processing with Python and NLTK
- 12 Lemmatization in Python | Natural Language Processing with Python and NLTK
- 13 WordNet Lemmatizer in NLTK python | Natural Language Processing with Python and NLTK
- 14 Vectorization in Python | Natural Language Processing with Python and NLTK
- 15 Count Vectorization in Python | CountVectorizer | Natural Language Processing with Python and NLTK
- 16 N-Grams Natural Language Processing | N-Gram NLP | Natural Language Processing with Python and NLTK
- 17 TF-IDF Vectorizer Python | Natural Language Processing with Python and NLTK
- 18 Feature Engineering | Natural Language Processing with Python and NLTK
- 19 Feature Engineering - Feature Creation | Natural Language Processing with Python and NLTK
- 20 Feature Evaluation | Natural Language Processing with Python and NLTK
- 21 Power Transformations | Box-Cox Transformation | Tukey Transformation
- 22 Evaluation Metrics: Accuracy, Precision and Recall | NLP NLTK
