AppliedAI

Hari Nair We can build complex web applications using Python. For that, we would need one of the third party Python web framework Flask . e:\python> pip install flask # flask #web2.py from flask import Flask app=Flask(__name__) @app.route("/") def hello():     return "Hello Chennai" e:\python> set FLASK_APP=web2.py to run the app server e:\python> flask run open browser and goto http://127.0.0.1:5000/ Another example #web4.py from flask import Flask , render_template app= Flask(__name__) @app.route("/") @app.route("/home") def home():     return render_template('home.html') @app.route("/about") def about():     return render_template('about.html') @app.route("/home2") def home2():     return render_template('home2.html') @app.route("/isdeep") def isdeep():     return render_template('isdeep.html') if __name__ == '__main_...

  Hari Nair Needing insurance is like needing a parachute. If it isn't there the first time, chances are you won't be needing it again. --Author unknown Building customer relationships and managing risks are key for Insurance companies. Insurance companies are making extensive use of AI  are reaping the benefits of increased customer satisfaction adding to their bottom line.  AI has the potential to transform the insurance experience for customers from frustrating and bureaucratic to something fast, on-demand, and more affordable. Tailor-made insurance products will attract more customers at fairer prices. If insurers apply AI tech to the mountain of data at their disposal, we will soon start to see more flexible insurance such as on-demand pay-as-you-go insurance, and premiums that automatically adjust in response to accidents, customer health, etc.   Insurers have yet to unlock the full potential of AI. Machine learning use cases in Insu...