Do’s and don’ts for fine-tuning on multifaceted NLP tasks

Lessons Learned

First, check your assumptions

Leverage the almighty BERT for your next NLP project

A tutorial using pandas, matplotlib, and seaborn to produce digestible insights from dirty data

In-Depth Analysis

Can word embeddings of article titles predict popularity? What can we learn about the relationship between sentiment and shares? word2vec can help us answer these questions, and more.

Sentiment distributions for popular news websites
  • Preprocess/clean the text data, using NLTK
  • Use word2vec to create word and title embeddings, then visualize them as clusters using t-SNE
  • Visualize the relationship between title sentiment and article popularity
  • Attempt to predict article popularity…

Charlene Chambliss

Machine Learning Engineer at Primer AI. I’m on Twitter @blissfulchar, and here’s my LinkedIn:

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