Machine Learning Final Year Projects

By: Engineer's Planet

The following topics are designed specifically for students in their final year of study in Computer Science and Engineering (CSE), encompassing both Bachelor’s (Btech) and Master’s (Mtech) degrees. The program adheres to the guidelines established by the Institute of Electrical and Electronics Engineers (IEEE) and centers on machine learning initiatives that are pertinent to the academic curriculum and professional aspirations of students in the year 2024. Machine Learning Final Year Projects

Develop a product recommender system by gathering and preprocessing order data, choosing an algorithm, splitting data, and training the system for accurate recommendations.

1. NutriGro (Building a Recommender System)

This project develops a shopping recommender system to enhance customer experience by suggesting personalized products, increasing engagement, boosting sales, and driving repeat purchases in e-commerce.

2. Product Recommendation Intelligence

This project uses deep learning to predict manufacturing faults, specifically faulty tires, by analyzing process data. This improves production efficiency, reduces waste, and optimizes manufacturing processes.

3.  Tyre Fault Prediction with Machine Learning

This project uses NLP to analyze text reviews, predicting emotional intensity (happiness, anger, or sadness). This helps optimize processes and enhance overall customer satisfaction by understanding sentiment in feedback.

4.   Intensity Analysis

This project builds a propensity model to forecast customer purchase likelihood, optimizing marketing efforts by leveraging valuable, data-driven insights from statistical analysis.

5. Propensity Model for Target Group Marketing Response

Conclusion:  These machine learning projects leverage advanced techniques. By harnessing data-driven insights, companies can proactively address challenges, reduce waste, and foster customer satisfaction, ultimately driving growth and long-term success.