• A. Rohith Reddy
• K. Vishnu Vardhan
• D. Sreevalli
• Arfa Mahvish

In this paper, a real-time ML-based system was built for farmers' eco-friendly recommendation system, Agriculture is the largest source of livelihood in India. Climate plays a crucial role in agriculture production. It has a profound influence on crop growth, development, and yield. Choosing the best crop to the given climatic conditions can increase the yield of a farmer. Farmers need a guide to help them in terms of crop suggestions and recommendations based on the amount of rainfall, soil pH, humidity, and temperature. We want to aid the farmers in this aspect by suggesting to them the type of crop to cultivate and also recommend fertilizers for that crop. Our project aims to build a web application that uses a machine learning model to predict the suitable crop to the given weather conditions. We would also recommend the use of organic fertilizers to improve the fertility of the soil and produce ec0-friendly crops. Our model is trained using the MLP algorithm, this algorithm uses 100 hidden layers to give the result. We chose this algorithm because it provides greater accuracy than other algorithms. Our model is trained with 3000 records consisting of data of various crops. The accuracy of our model is 94.71%.

MLP Classifier, Crop Recommendation Dataset, Gradient descent, SoftMax

"Farmer Eco Friendly Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 6, page no.b441-b445, June-2021, Available :http://www.jetir.org/papers/JETIR2106197.pdf

"Farmer Eco Friendly Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 6, page no. ppb441-b445, June-2021, Available at : http://www.jetir.org/papers/JETIR2106197.pdf