Internship Projects

About the Project
Manually classifying large image datasets is time-consuming, prone to errors, and costly. Extracting valuable insights from unstructured image data for analytics can be difficult. By using pre-trained machine learning models, we can efficiently classify images for various applications, making the process faster, more accurate, and cost-effective.

Learning Outcomes

Learn the fundamentals of image classification and its applications in real-world scenarios. Gain hands-on experience using pre-trained models to classify images effectively.
Develop skills in preparing and processing image data for machine learning tasks.

About the Project
This project aims to minimize manual errors, enhance attendance accuracy and verify the authenticity of student or staff attendance in classrooms and workplaces. The system automates the attendance process, ensuring reliability and efficiency while saving time compared to traditional methods.

Learning Outcomes

Learn the fundamentals of face recognition and its applications in automation.
Develop skills in designing automated systems for attendance management.

About the Project
Sorting through a large number of daily emails manually is time-consuming and inefficient. By utilizing Natural Language Processing (NLP) and machine learning, this project aims to create an automated system to filter spam emails effectively.

Learning Outcomes

Understand how NLP techniques are used to analyze and process text data from emails.
Learn how machine learning models are trained to classify emails as spam or important.

About the Project
This project aims to build a conversational chatbot capable of interacting with users, understanding their queries, and delivering appropriate responses. By using Natural Language Processing (NLP) techniques, the chatbot will process natural language inputs, interpret user intent and provide replies.

Learning Outcomes

Understand the basics of chatbots and their applications in various industries.
Learn NLP techniques like tokenization, intent recognition, and entity extraction.
Develop skills in designing logical and natural conversational flows for a chatbot.

About the Project
Retail businesses gather large amounts of shopping data from various channels like in-store and online platforms. However, analyzing this data to uncover trends, customer preferences, and seasonal buying patterns can be challenging. This project focuses on providing a data-driven solution to analyze shopping data, identify emerging trends and help teams to make informed decisions in operations and marketing.

Learning Outcomes

Learn how to gather and combine data for comprehensive analysis.
Gain skills in using visualization and statistical techniques to identify patterns and insights from retail data.

About the Project
Farmers often face challenges in identifying plant diseases early, leading to delayed actions, overuse of chemicals, and reduced crop yields. To address these issues, this project focuses on developing an intelligent, automated plant disease detection system using computer vision and machine learning. The system will accurately detect diseases in real time, enabling farmers to take prompt and targeted measures.

Learning Outcomes

Understand how computer vision techniques are applied in agriculture for plant disease detection.
Learn to collect and preprocess plant images for training a machine learning model.
Gain skills in building and training machine learning models to classify plant diseases.

About the Project
Understanding human movements and body postures is crucial in fields like sports performance analysis, healthcare monitoring and surveillance. However, accurately analyzing these movements poses significant challenges. This project focuses on implementing a structured approach to Human Pose Estimation using machine learning. The solution involves collecting and preprocessing data, performing feature engineering to extract key attributes, selecting the most suitable model, and training and evaluating it for accuracy and reliability.

Learning Outcomes

Learn the fundamentals of pose estimation and its applications in various domains.
Gain skills in collecting, cleaning, and preprocessing pose-related datasets for machine learning tasks.
Explore algorithms like CNNs or pre-trained models and learn how to train them for pose estimation tasks.