# Named Entity Recognition
**Named Entity Recognition** is a key task in Natural Language Processing. The process of detecting a word or a group of words that can be classified into known categories like person name, geographical location, date, numerical values, units of measurement, product names, etc. 

For eg. in the sentence, "Rahul is looking at Taj Mahal, which is one of the 7 wonders of the world." Rahul is a person's name, Taj Mahal is a monument, 7 is a numerical value. So, these 3 known categories can be detected as part of Named Entity Recognition.

# Packages used
* Tensorflow - for Named Entity Recognition task
* Numpy - for scientific calculations
* Pandas - loading CSV dataset and data wrangling
* Matplotlib - plotting and visualization

One can replicate the same results by following these steps:
1. Downloading this jupyter notebook on Google Colab. Alternatively, they can also load the dataset to their own computers instead of using Google Drive (as done in this notebook).
2. Running all the cells **sequentially** in the order as in the notebook.
3. It's done! You can go ahead and try the same algorithm on different datasets.
