• Sheetal Sawant
• Prashant VIshwakarma
• Parmendra Yadav
• Poonam Thakre

All ,individuals like to cook however they have no clue on what to cook and how to cook. Moreover, they likewise wish to know certain plans that suit their inclination. There are many cooking formula sites however the majority of them don’t give ideas to the client dependent on the client’s food inclinations. Momentum formula ideas created, and fixings content. The fundamental goal of the proposed application is to recommend a client-favored formula utilizing a Long short-term memory Algorithm. A long term short memory (LSTM) will be applied to distinguish the plans that have high opportunities for client to be like. This calculations will actually want to suggest plans dependent on client collaboration. The outcomes from the examination led to show that the proposed calculation is successful for prescribing favored plans to clients..

Food Inclinations, Long Term Short Memory (LSTM), client, plans

"Befit-Recipe Quantity Prediction Using LSTM Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 5, page no.g211-g216, May-2021, Available :http://www.jetir.org/papers/JETIR2105826.pdf

"Befit-Recipe Quantity Prediction Using LSTM Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 5, page no. ppg211-g216, May-2021, Available at : http://www.jetir.org/papers/JETIR2105826.pdf