What will you Learn in the Project?
- Exploratory Data Analysis and Preprocessing for Topic Modelling
- Latent Semantic Analysis for Topic ModellingÂ
- TSNE [T-distributed Stochastic Neighbor Embedding]Â
- Latent Dirichlet Allocation for Topic ModellingÂ
- Visualizing the topics in the form of clustering
Tools & Technologies Used
- Pandas
- Scikit-learn
- BokehÂ
- NumpyÂ
- MatplotlibÂ
Tasks Performed
This project is divided into multiple tasks.
- Import the necessary libraries and load the dataset
- Perform Exploratory Data Analysis for data understanding
- Display the top words in the dataset based on the frequency
- Preprocess the dataset before topic modeling
- Get the top topic using LSA (topic modeling)
- Display the embedding of the topics using TSNE
- Get the top topics using LDA (topic modeling)
- Display the embedding of the topics using TSNE
- Compare the results and state the best one
Course Content
Tasks
Not Enrolled
Skills you will develop
Topic Modelling
Latent Semantic Analysis for Topic Modelling
TSNE [T-distributed Stochastic Neighbor Embedding]
Latent Dirichlet Allocation for Topic Modelling
Visualizing the Topics in the form of Clustering
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