DEMYSTIFYING NATURAL LANGUAGE PROCESSING (NLP) WITH FLASK WEBAPP USING CUSTOM ML MODEL,API, AND PACKAGES(PART-2): EXPLAINING THE API MODEL AND PYTHON PACKAGES/MODULES USED FOR THE SENTIMENT WEBAPP
INTRODUCTION
GOAL: This project explains the API used to get sentence sentiment, emotions and category, and the python modules/ packages used to get word sentiment and summarize text in the flask webapp.
FLASK WEBAPP: https://kingofsentiments.herokuapp.com/
OUTLINE:
1. IBM API USED TO GET ,SENTIMENTS , EMOTIONS , AND CATEGORIES OF SENTENCE KEYWORDS AND ENTITIES IN THE FLASK SENTIMENT WEBAPP:
2. EXPLANING THE PYTHON MODULE USED TO GET WORD SENTIMENT IN THE FLASK WEBAPP
3. EXPLANING THE PYTHON MODULE USED TO SUMMARIZE SENTENCES IN THE FLASK WEBAPP.
1. IBM API USED TO GET ,SENTIMENTS , EMOTIONS , AND CATEGORIES OF SENTENCE KEYWORDS AND ENTITIES IN THE FLASK SENTIMENT WEBAPP:
API
API is the acronym for Application Programming Interface, which is a software intermediary that allows two applications to talk to each other. Each time you use an app like Facebook, send an instant message, or check the weather on your phone, you’re using an API.
What Is an Example of an API?
When you use an application on your mobile phone, the application connects to the Internet and sends data to a server. The server then retrieves that data, interprets it, performs the necessary actions and sends it back to your phone. The application then interprets that data and presents you with the information you wanted in a readable way. This is what an API is — all of this happens via API.
Example of Popular APIs: Google Maps, AcuuWeather, Youtube , Twitter…
Example of popular APIs used in AI : Alexa Skill Management API, Google Assistant API, IBM Watson Discovery API, SummarizeBot API, CarNet API etc
IBM Natural Language Understanding API was used to analyse the text and get the , Emotions, Category of keywords and entities of the sentence In the Flask webapp.
STEPS
1.1 We first check the documentation of the API to know how to use it in a programming language
link to documentation: https://cloud.ibm.com/apidocs/natural-language-understanding?code=python#sentiment
1.2. We import neccesary libraries needed in python to use the IBM API
1.3. Input your IBM IAMAuthenticator credentials and call The IBM Natural Language Understanding API via an ENDPOINT.
NB: you get this credentials from your account after you sign up on ibm
1.4. Use it to get Sentiment , Emotions, Category of keywords and entities from a text sentence and print out result.
2. EXPLANING THE PYTHON MODULES USED TO GET WORD SENTIMENT IN THE FLASK WEBAPP
I installed the Vader library to use to get the sentiment from a word.
Readmore about the vader library here: https://www.geeksforgeeks.org/python-sentiment-analysis-using-vader/
3. EXPLANING THE PYTHON MODULE USED TO SUMMARIZE SENTENCES IN THE FLASK WEBAPP.
I installed the gensim library to summarize sentences.
Readmore about the gensim library here: https://pypi.org/project/gensim/
4. CONCLUSION
This project explained how to use a web API for NLP .eg. IBM Natural Language Understanding API ,and how to use python modules like vader and gensim libraries for sentiment and summarization as used the webapp
WRITER: OLUYEDE SEGUN . A(jnr)
Explanatory Notebook and dataset:
https://github.com/juniorboycoder/FLASK_SENTIMENT_wEBAPP
Resources used (References):
LINK TO PART-3 (FINAL PART): https://juniorboyboy2.medium.com/demystifying-natural-language-processing-nlp-with-flask-webapp-using-custom-ml-model-api-and-1f7953cfb800
linkedin profile: https://www.linkedin.com/in/oluyede-segun-jr-a-a5550b167/
twitter profile: https://twitter.com/oluyedejun1
TAGS: #NLP #NLTK #Sentiment #MachineLearning #API #IBM #FLASK
