Natural Language Processing (Part 2): Data Cleaning & Text Pre-Processing in Python
Вставка
- Опубліковано 6 жов 2024
- 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
All of the supporting Python code can be found here: github.com/ada...
This was so clear and useful. We need more teachers like you!
pro tip: watch series on flixzone. Been using it for watching lots of of movies recently.
@Sterling Ronnie Definitely, been watching on Flixzone for since december myself :D
@Sterling Ronnie Definitely, I've been using Flixzone for months myself =)
this was so clear...i wish i found this 2 months before i started my NLP project lol
I love your explanations! Please do more data science videos!
You are the best teacher I’ve seen on this platform. Thank you 🙏
Well illustrated! Thanks for putting this together, Alice.
Great Work Alice .........keep posting these videos of NLP ....you are the only one on UA-cam that make sense. Love
AWESOME and one of the best explanations out there! would love to see you continue with more videos
this is good! was literally falling asleep with the other youtube videos on this topic, then yours came on! excellent! thanks.
Wow you are THE best tutor for ML. Thank you so much
Amazing explanations! Thank you!
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
Forgot some important, very clear in topic and subtopic, also roadmap (part 1-6)
Great explanation. Please grow your channel and make more videos.
Very good quality content.
Well explained!
Muchas gracias!
This is amazing.. thanks alot ⚘
great work really!!!
Very helpful! Thanks!
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?
Prefect job, super helpful. BTW do you have plan to do a Chinese NLP project?
you are amazing!
You are awesome
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(), columns=cv.get_feature_names())
Your just awsome
if there are to generate distractor based on question and answer dataset?
I encountered errors like. Lower is not a function etc
I just could do the Tutorial until thisd part
ModuleNotFoundError Traceback (most recent call last)
in
----> 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
you need to read the error message... it says you have not downloaded WordCloud. Alice explains how to do this in the introduction ('Read Me') here github.com/adashofdata/nlp-in-python-tutorial
😍