Day 49: 60 days of Data Science and Machine Learning Series

Yellowbrick for NLP…

Yellowbrick combines scikit-learn with matplotlib and provides the scikit-learn API to produce visualizations for the machine learning workflow. A good reference point to understand the vastness of Yellowbrick and how to use it —

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You can install yellowbrick using the command below —

$ pip install yellowbrick

In this post, we will analyze the text data using Yellowbrick and assess document similarity, topic modelling etc that are predicated on the notion of “similarity” between documents.

Import necessary libraries

from sklearn.feature_extraction.text import TfidfVectorizer
from yellowbrick.text import TSNEVisualizer

Load Corpus

from textDB import load_data
corpus = load_data('hobbies')
corpus.categories

Output —

['books', 'cinema', 'cooking', 'gaming', 'sports']

Vectorize the Documents

vec = TfidfVectorizer()
docs = vec.fit_transform(corpus.data)
labels= corpus.target
docs.shape

Output —

(448, 21379)

Cluster Similar Documents

# Euclidean Distance

tsne = TSNEVisualizer(size=(700,500),metrics = 'euclidean')
tsne.fit(docs,labels)
tsne.poof()

Output —

Manhattan Distance

#cityblock

tsne = TSNEVisualizer(metic = 'cityblock',size = (700,500))
tsne.fit(docs,labels)
tsne.poof()

Output —

Bray Curtis Dissimilarity

#braycurtis

tsne = TSNEVisualizer(metric='braycurtis',size=(700,500))
tsne.fit(docs,labels)
tsne.poof()

Output —

Canberra Distance

tsne = TSNEVisualizer(metric='canberra',size=(700,500))
tsne.fit(docs,labels)
tsne.poof()

Output —

Cosine Distance

tsne = TSNEVisualizer(metric='cosine',size=(700,500))
tsne.fit(docs,labels)
tsne.poof()

Output —

Learnings —

How to vectorize text data using TF-IDF and clustering documents using embedding techniques

Day 50: Coming soon!

Follow and Stay tuned. Keep coding :)

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Custom Layers in Keras

That’s it fellas. Peace out and keep coding :)

Stay Tuned and of-course let me end this post with a quote by Steve Jobs ;)

“Your work is going to fill a large part of your life, and the only way to be truly satisfied is to do what you believe is great work. And the only way to do great work is to love what you do. If you haven’t found it yet, keep looking. Don’t settle. As with all matters of the heart, you’ll know when you find it.”