Tensorflow Based Projects for Final Year

By: Engineer's Planet

The blog "TensorFlow Based Projects for Final Year" showcases innovative AI and machine learning project ideas using TensorFlow, ideal for students. It covers topics like image recognition, natural language processing, and predictive modeling with practical applications.

NutriGro is a recommender system that suggests products based on user orders and health data. It involves data collection, preprocessing, model training, evaluation, and deployment to provide personalized, health-focused product recommendations.

1. NutriGro (Building a Recommendation System)

This project builds a propensity model to predict which customer groups are most likely to respond to marketing campaigns, enabling optimized targeting through data analysis and behavioral prediction techniques.

2. Propensity Model for Marketing Campaign Response

This project develops an intelligent recommender system to suggest personalized products based on customer preferences and browsing history, aiming to enhance user experience, increase purchases, and improve customer retention.

3. Recommender System for E-commerce

FaultFindy uses deep learning to predict faulty tyres in manufacturing by analyzing process data and images. It helps reduce waste, enhance quality control, and improve overall production efficiency through intelligent prediction.

4. FaultFindy (Faulty Tyre Prediction in Manufacturing)

Intensity Analysis uses NLP to classify emotions like happiness, anger, or sadness in text reviews. It improves customer insights by predicting emotional intensity, enhancing satisfaction through data-driven feedback analysis.

5. Intensity Analysis (Emotion Prediction Using NLP)

In conclusion, These machine learning and deep learning projects—ranging from recommender systems to fault detection and emotion analysis—demonstrate how AI can drive intelligent decision-making, enhance user experience, and optimize business operations across diverse industries.