“Create an effective comma split tabular database from customer studies off an effective relationships application on after the articles: first-name, history identity, years, city, state, gender, sexual positioning, welfare, quantity of loves, number of matches, day consumer entered the fresh software, and owner’s rating of application ranging from step 1 and you will 5”
GPT-step 3 failed to provide us with people column headers and you may gave you a dining table with every-most other row having no pointers and just 4 rows regarding real customers data. it provided all of us around three articles from passions once we was basically simply wanting one to, but to-be fair to GPT-3, we performed explore an excellent plural. All of that being told you, the information and knowledge they did develop for people isn’t half bad – brands and you will sexual orientations song on right genders, the fresh towns it offered us also are inside their right claims, and also the times slip within a suitable diversity.
Hopefully when we offer GPT-step three a few examples it will ideal know most beautiful swedish women in the world what the audience is appearing to own. Unfortunately, on account of product restrictions, GPT-step three are unable to understand an entire databases to learn and you can create artificial data out-of, so we can just only have several example rows.
“Would a comma broke up tabular databases having line headers from 50 rows regarding consumer investigation regarding an internet dating application. 0, 87hbd7h, Douglas, Trees, thirty five, il, IL, Men, Gay, (Cooking Decorate Studying), 3200, 150, , 3.5, asnf84n, Randy, Ownes, twenty-two, Chi town, IL, Men, Upright, (Powering Hiking Knitting), 500, 205, , step three.2”
- Post Date: 09 Feb, 2025