Predictive Analytics

Hello everyone, as 'Tickle of Taste' is food recipe blog that uses data to take individual ingredients and try to classify what they do and don’t go well with, perhaps they come up with variations that weren't considered before.

"With the combination of the ingredients and the process used to prepare them, it is something one can look at, then try to find out the flavor fits well together."

But using Predicative analysis in kitchen business will help me to understand the statistical model and forecasting techniques to understand the future and answer customer taste and trends. That’s because it’s not possible to boil down each ingredient and individually pair things together at random. However, the visual predictive analytics platform could allow to streamline and to process, while also coming up with some interesting new ideas.

In the massive kitchen world, you can’t try mixing up everything. You want to take it scientifically and say, based on our data generated, that we know these go well; so which other flavors can we find that will work as well?

Predicative Analytics not only helps to predict trends but also helps to manage food and drink with different shelf-lives, with sentiment analysis of review on social media and websites which helps to analyse consumer demands and trends and generate transparency.

Ultimately, Tickle of Taste wants to provide customers with interesting new foods they can cook – and predicting data is something that will play a crucial role. " We are essentially able to build new food paring that might not have been addressed by the audience on their own and we can push the boundaries of dishes and ingredients match together well.

As our analysis reveals, factors such as user’s history, social relations and trends followed have indeed a significant impact on how recipe are created and why certain type of recipes and ingredients are being used by user.

For instance, Users can help themselves to Pizza and Wine pairing. Where Pizza is essentially bread and melted cheese, two things which pair very well with wines. This explains, the addition of tomato base brings in lots of acidity, which high acidity, you want to avoid heavy tannin. Light to medium body red wines work well with most pizzas, which means you don't need to spend to much on oaked or reserve wine.

[Picture Credit- lifehacker.com]

In particular:

- The processing of information also correlates with the creation of potential knowledge.

- Styles, groups and ingredients demonstrate clear associations.

     -Only a few fractions of audience follow their own methods and have strong bias preference for types and categories of food.

-Associations exist between the social factors like content and posts.

-The popularity of ingredients and food styles depends on the season and their relative occurrence is easier to predict than the specific types of food.

-Approaches which rely on food preferences for each individual.

 

 

 

Bibliography

https://www.logility.com/blog/descriptive-predictive-and-prescriptive-analytics-explained/

https://books.google.co.uk/books?id=D2JXuSs3kioC

https://christophtrattner.com/pubs/food_production_ht2016.pdf

https://yandex.ru/tutor/subject/variant/?variant_id=264