Crime Prediction Using Machine Learning and Deep Learning | Python Final Year IEEE Project

Crime Prediction Using Machine Learning and Deep Learning | Python Final Year IEEE Project. 🛒Buy Link: https://bit.ly/40PUTX8 (or) To buy this project in ONLINE, Contact: 🔗Email: [email protected], 🌐Website: https://www.jpinfotech.org 🔬Our Proposed Project Title: Advanced Crime Prediction Using Machine Learning with Crime Forecasting and Categorization. 💡Implementation Code: Python. 🔬Algorithm / Model Used: Decision Tree Classifier and Bagging Classifier. 🌐Web Framework: Flask. 🖥️Frontend: HTML, CSS, JavaScript. 💰Cost (In Indian Rupees): Rs.3000/. 📘Project Abstract: 👉"Crime Prediction Using Machine Learning" is a comprehensive project developed in Python that employs Machine Learning algorithms, specifically the Decision Tree Classifier and Bagging Classifier, to predict and classify various crime categories in Portland, Oregon, USA, from the years 2015 to 2023. The dataset utilized for this project consists of 505,063 data points, with a focus on 20 distinct crime classes, including 'Larceny Offenses,' 'Motor Vehicle Theft,' 'Assault Offenses,' 'Drug/Narcotic Offenses,' and others. 👉The Decision Tree Classifier yielded impressive results, achieving a 98% accuracy on the training set and a 95% accuracy on the test set. Similarly, the Bagging Classifier demonstrated robust performance, achieving a 98% accuracy on the training set and maintaining a 95% accuracy on the test set. These high accuracies indicate the effectiveness of the machine learning models in predicting and classifying crimes. 👉The dataset encompasses 15 features, including address, case number, crime against category (Person, Property, or Society), neighborhood, occur date, occur time, offense category, offense type, open data latitude/longitude, open data X/Y, and offense count. These features provide a comprehensive and diverse set of information, enabling the models to make accurate predictions. 📌IEEE Base Paper Project Title: Crime Prediction Using Machine Learning and Deep Learning. 📌REFERENCE: VARUN MANDALAPU, LAVANYA ELLURI, PIYUSH VYAS, AND NIRMALYA ROY, “Crime Prediction Using Machine Learning and Deep Learning: A Systematic Review and Future Directions”, IEEE Access (Volume: 11), 2023. 🏷️tags: #python #pythonprojects #machinelearningproject #pythonprogramming #pythonprojectforbeginners #pythonprojectideas #pythonmachinelearning #machinelearning #machinelearningpython #finalyearproject #ieeeprojects #finalyearprojects #datascience #datascienceproject #artificialintelligenceproject #projects #deeplearning #deeplearningproject #computerscienceproject #deeplearningprojects #majorprojects #academicprojects #majorproject #crimeprevention #crime #predictions