If watching food videos after dinner could be classified as a hobby, I would have found it easy to answer for the numerous times I have been asked to share my hobbies. Well, I shared some of the other hobbies that do not top my list but are easier to share in a large gathering of friends, acquaintances and family.
If you are with me this far, as a Data Scientist I calculate statistically –
- 33.33% of the readers can relate to my hobby and it tops your list of hobbies as well.
- 33.33% of the readers have watched 5 mins of food videos at least once in the past 1 year.
- and the remaining readers have never heard of food videos and have now been introduced to cultivating this as a hobby.
Back to the story, I was watching food videos and I enjoy trying out new cuisines. My viewing pattern triggered the machine learning algorithm on the streaming platform and I was introduced to an easy pasta recipe.
The machine-learning algorithm got me to add items to my mundane grocery list that does not see much deviation. At this point, I am convinced by the algorithm to try my hand at cooking a new dish and am prepared to make the pasta sauce from scratch. On the weekend morning that followed, I found myself walking down an unfamiliar aisle of my regular brick and mortar grocery store. I had not explored the section earlier and I started with selecting my choice of pasta from the variety available. I was super delighted to find the ready-to-eat pasta sauce with the contents label listing all the raw ingredients that I was looking for adjacent to the pasta. This made my life easier and I ended up revisiting my grocery list to alter and adjust my lunch for the day. I ended up picking the ready-to-eat sauce along with the raw ingredients so that I could try this item when I require to get my meal together quickly on a rushed day.
Had the pasta sauce not been so conveniently placed on the same shelf as the pasta and had been placed under the section of bottled, canned or ready-to-eat items, it would probably not have made it to my cart.
As with all stories, there is an ending and learning to this one. Many of us fail to realize when machine learning algorithm affects us in our daily life. The placement of products in the various aisles from the check-out lane, offers and discounts marketed, the arrangement of items on the shelves in grocery stores are designed to ease the shopping experience and leverage machine learning models like — Market Basket Analysis, Affinity and Association Rules, Customer Segmentation, Bayesian Statistics to name a few.
I am glad for all the machine learning that is enhancing our daily life and making things like grocery shopping a seamless experience.
