We have some names of dishes. With our project, Internet should search for each dish's recipe, obtain five links, perform web scraping on each link, and with the use of deep learning model/ machine learning model it should classify each line in the webscraped data(1- if ingredient is there in the line, 0-if ingredient is not there in the line) for each of the 5 links and then we will feed only lines which are labelled as 1 to NER. NER will get list of unique ingredients and required quantity for each ingredient. So basically NER should label ingredients & quantity from each line.
As of now we have webscraped data already for 240 dishes & manually labelled it as 1 & 0. Now we want to fit ML/DL model so that in future whenever new file is given it will classify lines in that file.
After applying ML/DL model we want to apply NER on the labelled lines. After doing all these, deployment of the project should be done.
Attaching one csv file of the labelled data for reference.
7 freelancers are bidding on average ₹9357 for this job
HI THIS IS HARDIK A DATA ENTRY OPERATOR THIS WORK IS SUITABLE FOR ME AS I WORK IN LESS WAGES AND PROVIDE QUALITY WORK ALSO MY TYPING SPEED AND ACCURACY IS VERY GOOD