| elyase/geotext |
67 |
|
16 |
2 |
about 6 years ago |
4 |
July 30, 2018 |
12 |
mit |
Python |
| Geotext extracts country and city mentions from text |
| chiphuyen/MetroTwitter |
48 |
|
0 |
0 |
almost 7 years ago |
0 |
|
0 |
|
Jupyter Notebook |
| What Twitter reveals about the differences between cities and the monoculture of the Bay Area |
| shawn-terryah/Twitter_Geolocation |
35 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
|
Python |
| Geolocating twitter users by the content of their tweets |
| anhthuan1999/Vietnamese-News-Classification |
26 |
|
0 |
0 |
over 2 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| We use LSTM, BiLSTM, BERT and SVM with TF-IDF, Word2vec and Bag-of-words to classify this documents to positive (labeled as 1), neutral (labeled as 0) and negative (labeled as 2) |
| akshitvjain/restaurant-finder-featureReviews |
19 |
|
0 |
0 |
almost 6 years ago |
0 |
|
0 |
mit |
Python |
| Build a Flask web application to help users retrieve key restaurant information and feature-based reviews (generated by applying market-basket model – Apriori algorithm and NLP on user reviews). |
| Botfuel/benchmark-nlp |
13 |
|
0 |
0 |
over 8 years ago |
0 |
|
0 |
apache-2.0 |
|
| NLP benchmark test sentences and full results |
| AbeHandler/contracts_nlp |
9 |
|
0 |
0 |
about 11 years ago |
0 |
|
0 |
|
Python |
| Uses NLP methods to parse and classify contracts from The City of New Orleans |
| mattdsteele/hackomaha-council-agendas |
5 |
|
0 |
0 |
over 10 years ago |
0 |
|
2 |
|
Java |
| City Council Agendas |
