| NLP-kr/tensorflow-ml-nlp |
157 |
|
0 |
0 |
over 5 years ago |
0 |
|
5 |
|
Jupyter Notebook |
| 텐서플로우와 머신러닝으로 시작하는 자연어처리(로지스틱회귀부터 트랜스포머 챗봇까지) |
| wroberts/pygermanet |
38 |
|
1 |
0 |
about 8 years ago |
3 |
November 10, 2016 |
0 |
mit |
Python |
| GermaNet API for Python |
| MrJay10/banking-faq-bot |
22 |
|
0 |
0 |
over 8 years ago |
0 |
|
2 |
|
Python |
| This is retrieval based Chatbot based on FAQs found at a banking website. |
| siddgood/podcast-recommendation-engine |
19 |
|
0 |
0 |
about 3 years ago |
0 |
|
0 |
mit |
Jupyter Notebook |
| :microphone: Building a content-based podcast recommender system using NLP |
| ATEC2018/mpcnn-text-similarity |
11 |
|
0 |
0 |
almost 8 years ago |
0 |
|
2 |
|
Python |
| 基于MP-CNN的中文句子相似度计算 |
| sahands/pelican_article_recommender |
10 |
|
0 |
0 |
almost 8 years ago |
0 |
|
0 |
mit |
Python |
| Article recommendation system for pelican based on post similarity calculated using NLTK and scikit-learn's TFIDF vectorizer. |
| Nagakiran1/Semantic-Feature-generation-for-words |
9 |
|
0 |
0 |
almost 7 years ago |
0 |
|
0 |
mit |
HTML |
| Building a Natural language Responsive system by Preprocessing(removing stop words , numbers, urls and stemmming ) raw text, generating features for words, Extracting Entities(Named Entity Recognition) based on specific application, Feeding the preprocessed and required text to Deep Learning Neural Network which can generate a responsive sentence for the given sentence. |
| JackBurdick/cosine_similarity_tfidf_nltk |
8 |
|
0 |
0 |
almost 9 years ago |
0 |
|
0 |
apache-2.0 |
Jupyter Notebook |
| calculate tfidf and cosine similarity using nltk |
| willtscott/inquire-boulder-chatbot |
8 |
|
0 |
0 |
almost 7 years ago |
0 |
|
3 |
bsd-3-clause |
Jupyter Notebook |
| A chatbot that uses NLP on the Inquire Boulder FAQ text to provide answers to user queries. |
| shubham16394/Text-Similarity |
7 |
|
0 |
0 |
over 8 years ago |
0 |
|
1 |
|
Python |
| Text Similarity using BM25 algorithm and WordNet |
