Crop Recommender System Using Machine Learning Approach Python Final Year IEEE Project

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Crop Recommender System Using Machine Learning Approach | Python Final Year IEEE Project. • 🛒Buy Link: https://bit.ly/3QRi52V • (or) • To buy this project in ONLINE, Contact: • 🔗Email: [email protected], • 🌐Website: https://www.jpinfotech.org • 📌Project Title: Crop Recommender System Using Machine Learning Approach. • 💡Implementation Code: Python. • 🔬Algorithm / Model Used: Random Forest. • 🔬Algorithm / Model used for Crop Yield: Random Forest Regressor. • 🔬Algorithm / Model used for Crop Recommendation: Random Forest Classifier. • 🌐Web Framework: Flask. • 🖥️Frontend: HTML, CSS, JavaScript. • 💰Cost (In Indian Rupees): Rs.3000/. • IEEE Base paper Abstract: • Agriculture and its allied sectors are undoubtedly the largest providers of livelihoods in rural India. The agriculture sector is also a significant contributor factor to the country’s Gross Domestic Product (GDP). Blessing to the country is the overwhelming size of the agricultural sector. However, regrettable is the yield per hectare of crops in comparison to international standards. This is one of the possible causes for a higher suicide rate among marginal farmers in India. This paper proposes a viable and user-friendly yield prediction system for the farmers. The proposed system provides connectivity to farmers via a mobile application. GPS helps to identify the user location. The user provides the area soil type as input. Machine learning algorithms allow choosing the most profitable crop list or predicting the crop yield for a user-selected crop. To predict the crop yield, selected Machine Learning algorithms such as Support Vector Machine (SVM), Artificial Neural Network (ANN), Random Forest (RF), Multivariate Linear Regression (MLR), and K-Nearest Neighbour (KNN) are used. Among them, the Random Forest showed the best results with 95% accuracy. Additionally, the system also suggests the best time to use the fertilizers to boost up the yield. • REFERENCE: • SHILPA MANGESH PANDE, DR. PREM KUMAR RAMESH, ANMOL, B.R AISHWARYA, KARUNA ROHILLA, KUMAR SHAURYA, “Crop Recommender System Using Machine Learning Approach”, IEEE Conference 2021. • #python #pythonprojects #machinelearningproject #pythonprogramming #pythonprojectforbeginners #pythonprojectideas #pythonmachinelearning #machinelearning #machinelearningpython #finalyearproject #ieeeprojects #finalyearprojects #datascience #datascienceproject #artificialintelligenceproject #projects #deeplearning #deeplearningproject #computerscienceproject #deeplearningprojects #majorprojects #academicprojects #majorproject • Video content: • crop recommendation system using python, crop recommendation system kaggle, crop recommendation system using machine learning and iot, crop recommendation system using python github, crop recommendation system using machine learning github, crop recommendation system using machine learning kaggle, crop recommendation system using machine learning github, crop recommendation system using machine learning project, agro consultant intelligent crop recommendation system using machine learning algorithms, crop recommendation system to maximize crop yield using machine learning technique, crop monitoring and recommendation system using machine learning techniques, crop recommendation system using machine learning, crop prediction using machine learning github, crop yield prediction

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