NLP Text Cleaning and Preprocessing | Tokenization | Lemmatization | Sententizer | Paragraphizer

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Ever wonder what type of tools are necessary for cleaning text for natural language processing? Well, look no further since I cover the most IMPORTANT topics in NLP when it comes to text processing. From stemming to lemmatizing and tokenizing to paragraphizing, I cover it all in this short, quick tutorial on what you absolutely need to know.

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Watch Next?
NLP Sentiment Analysis → https://youtu.be/CzRrD76pnVY
RegEx → https://youtu.be/cLoH112nqGc

🔗 My Links 🔗
GitHub: https://github.com/SpencerPao/spencerpao.github.io
My Website: https://spencerpao.github.io/

📓 Requirements 🧐
Basic Python Knowledge
Code: https://github.com/SpencerPao/Natural-Language-Processing

⌛ Timeline ⌛
0:00 - Getting Started & Data
1:03 - Removing Punctuation
1:34 - Cleaning URLs
2:02 - Stop Words
3:03 - Reasons for Lowercase
3:58 - Tokenization
5:01 - Sentencizer
5:58 - Paragraphizer
7:25 - What is Stemming & Lemmatization
8:45 - Stemming Process
10:48 - Lemmatization Process

🏷️Tags🏷️:
Python, NLP, Natural Language Processing, Text Preprocessing, Jupyter Notebook, Tutorial, Machine Learning, Artificial Intelligence, Elon Musk, Wikipedia, Paragraph, Sentence, RegEx, Regular Expression, How to, Explaination, stopwords

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Видео NLP Text Cleaning and Preprocessing | Tokenization | Lemmatization | Sententizer | Paragraphizer канала Spencer Pao