CHOICE OF TECHNOLOGY AND DEPLOYMENT ENVIRONMENT
As a part of our assignment we decided to take the machine learning technology in our Travel agency. Despite being not the new technology, machine learning is the emerging one that can control the whole technology in the future.
How Machine learning step in to our travel agency?
Imagine when you enter to any travel booking agency’s website and you’ll be served with all the dishes you are looking for in just one single search. Sounds good aye?
The machine learning in our database will read the frequent customer’s data (without losing the data privacy) and work accordingly on the next visit. The activities like, types of hotels or restaurants a customer opt for usually, different services he commonly demands, the flights he normally books, the class of flights he books for – all these data are tracked and learned by the machine. Later, once this customer logins again, he don’t really want to filter the whole page to meet the right preference, instead, the machine will give the suggestions corresponding to previous searches.
This will give the customer an outstanding experience as they don’t want to scroll down and spend lots of time to filter their likely ones. Everything will be quick and prompt. As customer satisfaction increases, they will stick to this agency and suggest to their friends, thus deliver a significant growth in the business.
The environment here is the travel agency itself where a website is developed capable of reading the customer preferences. The web app is developed using different machine learning tools that can club together to get the final product that can understand what the customer looking for. This is a simple task for a professional program developer who can easily deploy machine learning tools in the website. This doesn’t cost any extra cash for buying any costly stuff like “Sofia” but just by implementing some ML tools in to the website. Some of the major ML deploying methods are:
Server-side methods: Create a microservice or integrate your ML model into your web backend directly,
Frontend-side methods: Tensorflow.js – that allows to run the ML models in the browser.
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My Findings 