NLP: Natural Language Processing

What are the fields of NLP?

1) Speech Recognition : Translation of spoken language into text

2) Natural Language Understanding : A computers ability to understand what we say ( i.e. Siri )

3) Natural Language Generation : The generation of natural language by a computer

What are the Major Challenges of NLP?

Challenges within NLP

What are all the different text pre-processing steps to perform different NLP Tasks?

There are many techniques used including stemming, lemmatization, noise removal, and normalization.

Text Preprocessing Techniques

What about pre-processing raw data with numbers?

A common challenge is how to remove numbers from a string in Pandas DataFrame column.

You can use the below code & define a suitable function for it, iterate that over the DataFrame:

text = re.sub(r'\d+', '', text)

I am able to import NLTK library but get errors while performing operations based on it? LookupError: Please use the NLTK Downloader to obtain the resource.

Practical Applications of NLP in Finance:

1. Scrapping preliminary and prospectus data

2. Searching documents for key target words: i.e. selecting forward guidance

3. You can apply NLP in many creative ways, the sky is the limit.

   Personally I believe this field is slightly more subjective and more prone to error as the specific data pulled must be coded and understood in precise context.