|
1 | 1 | # Healthcare, Finance & Law
|
2 | 2 |
|
3 |
| -Set of notebooks associated with topics covered Chapter 10 of the book. |
| 3 | +## 🔖 Outline |
| 4 | + |
| 5 | +To be added |
| 6 | + |
| 7 | + |
| 8 | +## 🗒️ Notebooks |
| 9 | + |
| 10 | +Set of notebooks associated with the chapter. |
4 | 11 |
|
5 | 12 | 1. **[BioBERT](https://github.com/practical-nlp/practical-nlp/blob/master/Ch10/01_BioBERT_Demo.ipynb)**: Here we demonstrate how to load and use BioBERT which is a pre-trained bio-medical language representation model for various bio-medical text mining tasks perform the task of text classification.
|
6 | 13 |
|
7 | 14 | 2. **[FinBERT](https://github.com/practical-nlp/practical-nlp/blob/master/Ch10/02_FinBERT.ipynb)**: Here we demonstrate how to load and use FinBERT and perform the task of text classification. It is built by further training the BERT language model in the finance domain, using a large financial corpus.
|
8 | 15 |
|
9 | 16 | 3. **[LexNLP](https://github.com/practical-nlp/practical-nlp/blob/master/Ch10/03_LexNLP.ipynb)**: Here we demonstrate how to use LexnLP to extract various types of information from legal contracts.
|
| 17 | + |
| 18 | +## 🖼️ Figures |
| 19 | + |
| 20 | +Color figures as requested by the readers. |
| 21 | + |
| 22 | + |
| 23 | + |
| 24 | + |
| 25 | + |
| 26 | + |
| 27 | + |
| 28 | + |
| 29 | + |
| 30 | + |
| 31 | + |
| 32 | + |
| 33 | + |
| 34 | + |
| 35 | + |
| 36 | + |
| 37 | + |
| 38 | + |
| 39 | + |
| 40 | + |
| 41 | + |
0 commit comments