Analysis On Indian Cuisine with Automated Facebook
Description of the Project
Scientists mined into a bunch of recipes and found out that the food-pairing hypothesis works well for any cuisine in the world — except the Indian one. Does automation have a place in hospitality, an industry built on human-to-human interactions?
While it may be a long way off before we see robots cleaning rooms or serving tables, one major area of growth in automation today is communications using bigdata analytics. Assisted automation in feedback responses: Advances in machine learning will soon make it technically possible to automate responses to online reviews and guest surveys. But that’s a risky proposition, especially in the case of negative feedback.
Visualization on Cricket stadiums
CricVis is a visualization tool that lets users interactively explore all ODI matches from the 2015 ICC World Cup. The skyline views at the top of the page summarize each inning of the match. Each rounded rectangle represents one delivery and the fill colors represent the key event associated with the delivery (runs, extras, wickets, and dot balls). Users can select an innings using the “Click for More” button resulting in inning-specific views that show, for each delivery, ball landing positions (pitch map), positions where the balls reached the batsman (stump map), and where the ball was hit (ground map). The rings along the circumference of the ground indicate scoring zones and the color indicates how many runs were scored in a zone (darker the color, more the runs scored). Individual players and their match statistics are displayed at the bottom of the screen.
PREDICTING MOVIE SUCCESS WITH BIG DATA IN THE FILM INDUSTRY
Data points to look out for It is not uncommon for certain movie trailers to go viral and a specific movie to be hyped about a lot, regardless of if it’s actually good. Today, such interests and curiosity can be accurately measured from different online sources including search engine results, social media feedback, video views we develop a recommender system for successful prediction and script analysis we use Jaccard’s and Cosine similarity measures using big data.