[PDF] Top 20 Implementation of Student Monitoring System using Machine Learning Algorithms
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Implementation of Student Monitoring System using Machine Learning Algorithms
... of student list who score below 10 marks in the internal ...the system which has access to the database which contains all the marks and the attendance details of the ...The system will automatically ... See full document
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IMPLEMENTATION AND ANALYSIS OF MACHINE LEARNING APPROACHES AND TECHNIQUES FOR STUDENT DROPOUT PREDICTION
... Supervised machine learning algorithms can apply what has been learned in the past to new data using labeled examples to predict future ...the learning algorithm produces an inferred ... See full document
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IoT based Agro Automation System using Machine Learning Algorithms
... built using ARM Cortex M0+ ...processing using NI myRIO was carried out by means of the NI LabVIEW ...time implementation as the simulation oriented initial approach eliminated almost all types of ... See full document
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Machine Learning Algorithms and Predictive Models for Undergraduate Student Retention
... J48 decision tree is an implementation of the C4.5 algorithm in the WEKA. C4.5 is an algorithm used to generate a decision tree developed by Ross Quinlan. C4.5 is an extension of Quinlan's earlier ID3 algorithm. ... See full document
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Heart Disease Detection by Using Machine Learning Algorithms and a Real Time Cardiovascular Health Monitoring System
... cardiovascular system which also contains lungs. Cardiovascular system also comprises a network of blood vessels, for example, veins, arteries, and ...Record System) which can be used for designing ... See full document
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Tracking student movement using active RFID
... - Monitoring students of Universiti Tun Hussein Onn Malaysia (UTHM) movement around the campus is difficult especially for lecturer hall and laboratory access ...By using RFID technology, it is easy to ... See full document
5
The Design of Hybrid Crop Recommendation System using Machine Learning Algorithms
... Recommendation system using an ensemble approach is implemented by ...type using a random tree, k-nearest neighbor and naive Bayes are combined as an ensemble ...and implementation of crop and ... See full document
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Patient Health Monitoring using IoT with Machine Learning
... by using machine learning ...for machine learning algorithms include decision tree classifiers, rule-based classifiers, adaboost classifiers, neural networks, support vector ... See full document
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Machine Learning: Introduction, Algorithms and Implementation
... Consider, a restorative conclusion routine trained with information from medical clinics everywhere throughout the world. Be that as it may, because of protection concerns, this sort of utilizations isn't generally ... See full document
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Smart Body Monitoring system using IoT and Machine Learning
... Clustering algorithms like KNN, and Support vector machine ...the system is very helpful for the facilitating the forecast methods, based on some restrictions like chest pain, cholesterol, age, ... See full document
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Perinatal Hypoxia Diagnostic System by using Scalable Machine Learning Algorithms
... and machine learning approaches in healthcare can help in improving clinical decision making and treatment by identifying and accumulating accurate ...(CTG) monitoring that helps in identifying the ... See full document
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Internet-Sensor Information Mining Using Machine Learning Approach
... streaming machine learning algorithms. The machine learning algorithm used is “vertical Hoeffding Tree” ...unsupervised machine learning ... See full document
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Virtual machine scheduling strategy based on machine learning algorithms for load balancing
... virtual machine executed a period of time, some tasks have been completed, and the virtual machine where these tasks were located would release the server resources, which might cause the ser- ver to be in ... See full document
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Student Future Prediction Using Machine Learning
... This system is a web application that would help students studying in high schools to select a course for their ...The system would recommend the student, a career option based on their personality ... See full document
5
A Pragmatic Supervised Learning Methodology of Hate Speech Detection in Social Media
... N-grams are one of the most used techniques in hate speech automatic detection and related tasks [1,3,14]. The most common n-grams approach consists in combining sequential words into lists with size N. In this case, the ... See full document
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Twitter Spam Detection Using Machine Learning Algorithms
... Bayes algorithms performs well for small data set and in this experiment we have applied Naive Bayes and Random algorithm for small data set and hence we have achieved better performance for Naive Bayes compared ... See full document
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A Framework for Vietnamese Email Phishing Detection
... detection system is ...of machine learning algorithms to improve the performance of phishing email detection in Vietnamese ...evaluated using two ... See full document
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A Review on Several Vulnerabilities Detection Techniques in Android Mobile
... A malicious activity has threatened smart phones for many years and android devices are gaining popularity with time. Seeing this most of the discovered vulnerabilities is aiming at android platform. A malicious activity ... See full document
12
Recommending Learning Path of Student using Machine Learning
... paper Learning Management System is build in which the automatic, dynamic, and global student modelling is done adaptive mechanism aims at being easy to use for teachers by being generic and ... See full document
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A Survey on Intrusion Detection Systems and Classification Techniques
... detection system (NIDS) is used to monitor and analyse network traffic to protect a system from network-based threats where the data is traffic across the ...and monitoring the network traffic ... See full document
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