Python IEEE Projects 2020 - 2021
A Machine Learning Methodology for Diagnosing Chronic Kidney Disease
Academic Performance Prediction Based on Multisource, Multifeature Behavioral Data
Artificial Intelligence and COVID-19: Deep Learning Approaches for Diagnosis and Treatment
Comparison of Machine Learning Algorithms for Predicting Crime Hotspots
COVID-19 Future Forecasting Using Supervised Machine Learning Models
Crop Yield Prediction based on Indian Agriculture using Machine Learning
Deep Learning Based Fusion Approach for Hate Speech Detection
Deep Learning for Large-Scale Traffic-Sign Detection and Recognition
Defensive Modeling of Fake News Through Online Social Networks
Detecting and Characterizing Extremist Reviewer Groups in Online Product Reviews
Detecting Spam Email With Machine Learning Optimized With Bio-Inspired Metaheuristic Algorithms
Detection of Fake and Clone accounts in Twitter using Classification and Distance Measure Algorithms
Detection of Malicious Social Bots Using Learning Automata With URL Features in Twitter Network
FAKEDETECTOR: Effective Fake News Detection with Deep Diffusive Neural Network
Finding Psychological Instability Using Machine Learning
Flight Delay Prediction Based on Aviation Big Data and Machine Learning
Heart Disease Identification Method Using Machine Learning Classification in E-Healthcare
Hybrid Feature based Prediction of Suicide Related Activity on Twitter
Intrusion Detection System Using PCA with Random Forest Approach
Performance Analysis on Student Feedback using Machine Learning Algorithms
Prediction of Breast Cancer, Comparative Review of Machine Learning Techniques, and Their Analysis
Rice Leaf Diseases Classification Using CNN With Transfer Learning
Spam Review Detection Using the Linguistic and Spammer Behavioral Methods
Students Performance Prediction in Online Courses Using Machine Learning Algorithms
A Mask Detection Method for Shoppers Under the Threat of COVID-19 Coronavirus
Email Spam Detection Using Machine Learning Algorithms
Detecting A Twitter Cyberbullying Using Machine Learning
A New Intelligent Approach for Effective Recognition of Diabetes in the IoT E-HealthCare Environment
