Currently reading articles under label: Book

Machine Learning ML Books

Favoured

MLAPP (Kevin Murphy), Machine Learning - A Probablistic Perspective, is more comprehensive, insightful and interesting, and contains more "real" examples/problems. However, the presents are kinda out of order, which can be difficult to follow for a first book.

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Sunny Summary

3 steps:

preprocessing.py preprocessing to extract: author, average sentence length, average word length, punctuation profile, sentiment scores, part-of-speech profiles/tags (only in code, not taken into the csv).

TFIDF.py content-wise k-mean......