Bhargav Srinivasa Desikan
where else to find them
github:bhargavvader
speakerdeck:bhargavvader
what they talk about
where they keep going back
- PyData Berlin2 editions2017–2018
on a stage with
never shared a talk
who talks about the same things
- Benjamin Batorsky3 talks
- Matthew Honnibal3 talks
- Vaibhav Srivastav7 talks
- Lev Konstantinovskiy8 talks
- Matti Lyra3 talks
- Nabanita Roy4 talks
| title | conference | date |
|---|---|---|
| Tips, Tricks and Topics in Text Analysis | PyData Los Angeles 2018 | 2018-10-17 |
Hands‑on pipeline that loads ~300 Australian news articles and a 20‑newsgroups subset, uses spaCy for lemmatization, POS and NER, builds bigrams, creates a… | ||
| Why You Should Do Text Analysis in Python (Even if You Don't Want to) | PyData Los Angeles 2018 | 2018-10-17 |
Exports of group chats from WhatsApp exports get parsed year by year to count who starts conversations who uses the most emojis and to run topic models that… | ||
| Tricks, tips and topics in Text Analysis | PyData Berlin 2018 | 2018-07-06 |
Pipeline shows concrete choices: spaCy for POS, NER and lemmatization, gensim LDA on a 300‑article news corpus to surface ~5–10 rough topics, scikit‑learn +… | ||
| Tricks, tips and topics in Text Analysis | PyData Amsterdam 2018 | 2018-05-25 |
Shows an actual pipeline: use the spaCy pipeline to tokenize, POS‑tag, lemmatize and mark stopwords, build bigrams with gensim, make a gensim dictionary/corpus… | ||
| Topic Modelling (and more) with NLP framework Gensim | PyData Berlin 2017 | 2017-06-23 |
Demo shows a complete pipeline: spaCy preprocessing (lemmatization, curated stopwords, bigrams) turns messy news text into a gensim-ready corpus; gensim runs… | ||
| nothing matches | ||