Python | NLP | LDA | Gensim Topic Modelling | PyLDAvis | Video 2/2
In this video, we will use Python,Gensim package and interpret the fitted LDA Model's topics using PyLDAvis.
We will use UFO Sightings dataset from Tidytuesday R Repository
Gensim:
radimrehurek.com/gensim
NLTK (Natural Language Toolkit):
www.nltk.org/
PyLDAvis:
pyldavis.readthedocs.io/en/latest/readme.html
Dataset:
github.com/rfordatascience/tidytuesday/blob/master/data/2023/2023-06-20/ufo_sightings.csv
Project Files:
drive.google.com/drive/folders/1KQu9Yjnb-2a9M71FM5M39S7l3rXFxt0F?usp=sharing
More datasets @Tidytuesday R
github.com/rfordatascience/tidytuesday
TIMESTAMPS
00:00 Intro to the basic concepts of Topic Modeling
02:23 About the Python Package Gensim
03:18 Over view the step by step coding process using Jupyter Notebook
04:50 About Tidytuesday R, the data source repository
06:37 Copy the csv file link and then paste it into the pd.read_csv() function
07:00 Step by Step Coding in the Jupyter Notebook
13:00 About the python package pyLDAvis
13:56 Visualize the Topic Model and interpret the topics in the model
16:25 Recap and conclusion
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