Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python

This six-part video series goes through an end-to-end Natural Language Processing (NLP) project in Python to compare stand up comedy routines.

- Natural Language Processing (Part 1): Introduction to NLP & Data Science
- Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
- Natural Language Processing (Part 3): Exploratory Data Analysis & Word Clouds in Python
- Natural Language Processing (Part 4): Sentiment Analysis with TextBlob in Python
- Natural Language Processing (Part 5): Topic Modeling with Latent Dirichlet Allocation in Python
- Natural Language Processing (Part 6): Text Generation with Markov Chains in Python

[okwuazuifeanyi]

You are the best teacher I’ve seen on this platform. Thank you 🙏

[coolsteven]

This was so clear and useful. We need more teachers like you!

[rubyjiang]

I love your explanations! Please do more data science videos!

[justinhuang]

this was so clear...i wish i found this 2 months before i started my NLP project lol

[chrisogonas]

Well illustrated! Thanks for putting this together, Alice.

[zoeyxster]

this is good! was literally falling asleep with the other youtube videos on this topic, then yours came on! excellent! thanks.

[Patriotpak]

Great Work Alice posting these videos of NLP ....you are the only one on YouTube that make sense. Love <3

[semidevilz]

AWESOME and one of the best explanations out there! would love to see you continue with more videos

[kavindudananjaya]

Wow you are THE best tutor for ML. Thank you so much

[bramaningds]

Hi... You doing great, it gave me a lot of insight, as beginner . However, it would be perfect if you could raise up the volume, it help me to get clear the context you talk about. THANKS

[abhishek-shrm]

Great explanation. Please grow your channel and make more videos.

[mdsdn]

hey great videos you got here but i have a question, so basically i need to semantically compare two sentences, say for example i receive a query and then compare it to a sample of phrases that i have to return the phrase that resembles the query the most. Any recommendations that you have for me?

[MiffyDad]

Prefect job, super helpful. BTW do you have plan to do a Chinese NLP project?

[NewtonSathavety]

if there are to generate distractor based on question and answer dataset?

[afsheenmaroof]

I encountered errors like. Lower is not a function etc

[rezaabdi]

Thanks a lot for these clean and informative videos, wondering if you have any suggestions to avoid memory failure in making Document-Term Matrix?!
Here in this line of your code:
data_dtm = pd.DataFrame(data_cv.toarray(),

[The_Wolf_AOE]

I just could do the Tutorial until thisd part


ModuleNotFoundError Traceback (most recent call last)
in <module>
----> 1 from wordcloud import WordCloud
2 from wordcloud import WordCloud
3 wc = WordCloud(stopwords=stop_words, background_color="white", colormap="Dark2",
4 max_font_size=150, random_state=42)

ModuleNotFoundError: No module named 'wordcloud'



I dont know what to do :( help! I'm Stuck