Undergrad Thesis on Machine Learning

Topic: Prediction of Crops Production using Machine Learning Algorithms

Abstract:  
  
The purpose of this study is to predict crop production using machine learning.  
The paper focuses on predicting the production of crops depending on temperature,  
wind speed, humidity, crop type, and harvestable area.  
  
We have used various machine learning models and compared the results.  
Results were compared against five models, Support Vector Machine (SVM),  
Naive Bayes, Multiple Linear Regression, K-Nearest Neighbor (KNN) and  
Random Forest. Out of which Random Forest yielded the highest accuracy score.  

Folders

Name	Description	Link
Documents	All the related documents	Click
Dataset	Dataset used in the thesis	Click
Jupyter Notebooks	All the algorithms	Click

Contributors:

Name	ID	Profile
Md. Jim Ar Rafi	181400083	JimArRafi10
A.S.M Imrul Kayes Bhuiyan	181400103	asmimrul007
Raihan Munim	181400138	raihanrms

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