Processing Text with Python Essential Training
In this course “Processing Text with Python Essential Training” on LinkedIn Learning, instructor Kumaran Ponnambalam helped in building text mining skill set, covering key techniques for extracting, cleansing, and processing text in Python. The instructor also reviewed key text processing concepts like tokenization and stemming. He also looked at techniques for converting text into analytics-ready form, including n-grams and TF-IDF, while providing useful examples of these techniques using Python and the NLTK library. Additional things that I got an overview from this course is how to interpret the relationship of documents inside a corpus, how to distinguish between the different text processing capabilities that the NLTK provides, explain why text cleansing and extraction occur when processing text with Python, apply advanced text processing steps to find and create TF-IDF and the TF-IDF array. Overall, this course is helpful in explaining the best practices to follow when processing text with Python.