Sreedev A
Bangaluru
Summary
An innovative B.Tech graduate in Artificial Intelligence and Machine Learning, combining a strong academic foundation with hands-on internship experience and a portfolio of impactful projects in computer vision and image analysis. Eager to apply expertise in deep learning and model development to solve complex, real-world challenges.
Overview
2
2
years of professional experience
Work History
Machine Learning Intern
Feynn Labs
10.2024 - 03.2025
- Conceptualized Matchify, an AI recruitment app that matches candidates to jobs based on skills, experience, and preferences using NLP and clustering models to analyze resumes and job descriptions.
- Led a market segmentation project, using K-means, KNN, and PCA to identify key customer groups based on purchasing behavior and demographics, improving model efficiency and interpretability.
- Developed an AI product prototype, using K-means, KNN, PCA, and Time Series Analysis for market segmentation and trend forecasting, while creating a financial model to estimate profitability.
AI & ML Intern
Aerobosoft
08.2023 - 10.2023
- Built and fine-tuned predictive models for Kyphosis Bone Cancer using algorithms like Support Vector Machines (SVM), Random Forest, and XGBoost with Scikit-learn.
- Implemented deep learning models with TensorFlow/PyTorch for advanced pattern recognition.
- Utilized Pandas and NumPy for data manipulation, handling missing values, scaling features, and encoding categorical variables.
- Employed Scikit-learn's preprocessing tools to prepare data for model training and evaluation.
Education
Bachelor of Engineering - Artificial Intellingence and Machine Learning
Acharya Institutes Of Technology
Bengaluru, India12.2024
Skills
- Python, Java, C, C
- HTML and CSS
- Pandas and Numpy
- TensorFlow and Scikit-learn
- OpenCV
- Communication skills
- Leadership abilities
- Team collaboration
- Creative thinking
- Emotional intelligence
- Problem solving
Websites
Projects
Detection of Cardiovascular Diseases Using Retinal Images, Developed a machine learning model to detect early signs of cardiovascular diseases by analyzing retinal images, using techniques such as image processing, feature extraction, and convolutional neural networks (CNNs) for automated diagnosis. Implemented a robust pipeline integrating data preprocessing, classification algorithms (e.g., SVM, Random Forest), and deep learning models to improve accuracy in detecting disease indicators from retinal features. AI Chatbot, Developed a chatbot with a user-friendly interface, integrating Natural Language Processing (NLP), intent recognition, entity extraction, and sentiment analysis to ensure accurate user interaction and improve conversational quality. Built and integrated multiple modules including Dialog Management, Knowledge Base, and Response Generation, utilizing machine learning models, deep learning algorithms, reinforcement learning, and API integration for real-time learning and continuous performance improvement. Real-Time Hand Gesture Recognition System, Developed a gesture recognition system using OpenCV and MediaPipe for real-time human-computer interaction. Conducted end-to-end functional and regression testing to ensure 98% response accuracy. Implemented test case documentation and bug tracking to support iterative improvements. Attendance Register ERP Android App, Built a Java-based Android application using Android Studio and SQLite for attendance management. Performed functional, integration, and UAT testing to validate app usability and data consistency. Designed and executed SQL queries for efficient database synchronization.
Timeline
Machine Learning Intern
Feynn Labs
10.2024 - 03.2025
AI & ML Intern
Aerobosoft
08.2023 - 10.2023
Bachelor of Engineering - Artificial Intellingence and Machine Learning
Acharya Institutes Of Technology