Mini Project

https://docs.google.com/presentation/d/1NvVlWmd5B-u5iyuf7N63qGazy3lxZpbp/edit?usp=sharing&ouid=112711162618141236570&rtpof=true&sd=true

https://docs.google.com/presentation/d/1DpdiE5eXijUf4JNxXoMx2eLl79MnUanj/edit?usp=sharing&ouid=112711162618141236570&rtpof=true&sd=true

https://drive.google.com/file/d/1JDgDAB3Iy82z9Lz3jf1kRefSgjC5QpWY/view?usp=sharing

https://docs.google.com/document/d/1TglDn6B5B57q6M7zczYCCXbaSr34fe_P/edit?usp=sharing&ouid=112711162618141236570&rtpof=true&sd=true

The project, titled AI-Based FAQ Chatbot with Voice Assistance, is an intelligent, user-friendly system that utilizes artificial intelligence and natural language processing to answer frequently asked questions while incorporating voice assistance to enhance user interaction and accessibility.

 

https://drive.google.com/file/d/1u1c6KJonPvQLNlNNT8Ds9LWEV0IzbuRv/view?usp=sharing

The project is titled ANALYSIS AND CLASSIFICATION OF FAKE NEWS USING SEQUENTIAL PATTERN MINING. It introduces a novel framework called FNACSPM that utilizes sequential pattern mining (SPM) to extract frequent linguistic patterns from diverse datasets, which are then used as features for the accurate and efficient classification of fake news. 

https://drive.google.com/file/d/1V9G3itl05ogM7llnXJU6bc9jEyDiHJ9W/view?usp=sharing

The project is titled "Smart Medical Diagnosis of CKD Using Data Mining Techniques" and it focuses on utilizing machine learning and data mining algorithms to analyze patient medical records for the early detection and stage prediction of Chronic Kidney Disease (CKD).

   

https://drive.google.com/file/d/1GILKVJr1M7l3-grvpkznqj0nZwO2SR9T/view?usp=sharing

The project is named An Intelligent Clipboard Management System for Enhanced User Productivity, and it is a web-based platform that automatically monitors, captures, and stores clipboard activity in a structured SQLite database to prevent data loss and allow users to view, search, and organize their clipboard history.

 

https://drive.google.com/file/d/1nIk-CmbQjm9z6-pld8pXDFrh8n_PQmKV/view?usp=sharing

The project is titled Customer Behaviour Analysis and Predictive Modeling in Supermarket Retail: A Comprehensive Data Mining Approach. It utilizes advanced data mining and machine learning techniques, such as K-Means clustering and regression models, to analyze supermarket transactional data to predict customer behavior, optimize business strategies, and enhance customer satisfaction. 

https://drive.google.com/file/d/1mBec9uUvfKPUJfRO1dXIieazlSqWt36-/view?usp=sharing

The project is titled "A Bidirectional Encoder Representations from Transformers (BERT)-Based Dense Retrieval Approach for Open-Domain QA". It introduces Dense Passage Retrieval (DPR), a system that utilizes dual BERT-based neural encoders to convert questions and text passages into dense embeddings (numeric vectors) to find accurate answers based on semantic meaning rather than simple word-matching.

 

https://drive.google.com/file/d/1IU34B4ZMBPZicfr2o4frBWPgAzty2fOW/view?usp=sharing

The project is titled Electric Vehicle Adoption Trends in India. It focuses on examining recent trends, drivers, and challenges in electric vehicle (EV) adoption across various segments in India, while also providing data-driven market forecasts and strategic recommendations for achieving sustainable mobility.

 

https://drive.google.com/file/d/14LX4p2mPQqJInjh0sbTsn3nAAtu6_z4s/view?usp=sharing

The project is titled EMOTION BASED MUSIC RECOMMENDATION SYSTEM USING MACHINE LEARNING, and it is designed to automatically generate music playlists by detecting a user's emotional state through either wearable physiological sensors or facial image analysis to enhance recommendation accuracy and reduce manual effort.

 

https://drive.google.com/file/d/1tpUqCRZKgsJ7yWBtXLeWLOKsOF8iJxJy/view?usp=sharing

The project is titled "Machine Learning-Based Credit Card Fraud Detection Using Random Forest and Classification and Regression Trees". It is a system designed to utilize supervised machine learning algorithms, specifically Random Forest, to analyze transaction datasets and accurately identify fraudulent activities in both online and offline environments.

 

https://drive.google.com/file/d/1Un7WwnQL4heFs7MipdQi74I8qPXfm9IP/view?usp=sharing

The project is titled "Exploring the Fusion Potential of Data Analytics in the Process of Mining Digitalization". It is an intelligent, data-driven system that integrates statistical data analytics, machine learning-based fault classification using a Random Forest classifier, and interactive data visualization within a unified graphical interface to automate and improve surface fault analysis in mining operations.

 

https://drive.google.com/file/d/1QiFVH4cunyfhKnAIp0JK8QfLbwrTZHrO/view?usp=sharing

The project is titled Smart Control of Traffic Light Using Artificial Intelligence. This system utilizes live imagery from junction cameras and YOLO object detection algorithms to estimate real-time traffic density, automatically adjusting traffic light timings to reduce congestion and wait times.

 

https://drive.google.com/file/d/1Mv04a_d_4zkej0S99D24bkC3oD-xJmCy/view?usp=sharing

The project is titled Secure Expense Tracking and Analysis System, also referred to as the Smart Expense Tracker. It is a lightweight, Python-based desktop application that provides a secure, offline platform for users to record, categorize, and analyze daily expenses through interactive visualizations and detailed reports.

 

https://drive.google.com/file/d/1ofvuyf2ykmwjOJpcwU7yYSPWMQrmVzhv/view?usp=sharing

The project is titled "A Machine Learning Approach for Identifying Fake Social Media Profiles". It utilizes an Artificial Neural Network (ANN) to analyze key profile features—such as account age, gender, activity levels, and location data—to determine the authenticity of social media friend requests and provide a proactive defense against fraudulent profiles and automated bots.

 

https://drive.google.com/file/d/1O3ttNNXiIJalJeGXmDeF2AlRqBwZlMXH/view?usp=sharing

The project is titled "WEATHER DATA DASHBOARD USING MATPLOTLIB & PLOTLY". It is a centralized analytical platform designed to automate the collection, processing, and visualization of real-time and historical weather data using Python-based libraries to provide researchers, farmers, and urban planners with dynamic, interactive insights into climate trends such as temperature, humidity, and rainfall.

 

https://drive.google.com/file/d/1fVuAjckoZzu52xJz7u0P_OEs8m88Rlk1/view?usp=sharing