KEERTHANA BM

"As an MS student in Data Management and AI, with 7 years of experience in semi-technical roles and recruitment, I am passionately transitioning into AI and data management. My expertise in machine learning, big data, and business intelligence, combined with my strong analytical mindset, positions me to contribute innovative data-driven solutions. I am eager to apply my skills in a dynamic internship, collaborate with experts, and make a meaningful impact while accelerating my growth in the AI field."

• GenAI Foundation
• GitHub CoPilot L1 V1
• Project Management Professional
• AWS Database Migration
• AI White belt L1 V1 (Google Cloud Computing Fundamentals)

• Received the "STAR PERFORMER" award for the best performance (Achieved beyond the target) in 2018.
• Received the "PAT ON BACK" award in 2019, 2020, and 2021 for three consecutive years for best performance.
• Received "EXTRA MILE" in 2022.
• Received appreciation from the Client side for quick support during escalation.
• Received "Standing Ovation "for exemplary performance during presentation

Real-Time Drug Review Sentiment Analysis

Technologies Used: Python, TensorFlow, Keras, Streamlit, PIL, Numpy, OS, Jupyter

• Developed a sentiment analysis application for drug reviews that predicts sentiment (Positive, Neutral, Negative) from user input using deep learning models (CNN and LSTM)
• Utilized TensorFlow and Keras for training and deploying a sentiment classification

model with text data.

• Integrated image-based feedback to visually represent sentiment predictions, using PIL for image processing.
• Created an intuitive Streamlit web interface for real-time sentiment prediction, accepting both text and numerical input.
• Used Numpy for efficient data handling and OS for file management to load sentiment-based images from a local directory.
• Developed a custom tokenizer and sequence padding for text preprocessing before feeding input into the model for predictions.
• Implemented error handling and validation to ensure robustness and accurate results.

Real-Time Stock Market Price Prediction and Visualization

Tools: TensorFlow, Keras, Yahoo Finance API, Streamlit

• Developed a real-time stock market price prediction model using LSTM for time-series forecasting.
• Integrated historical data and live stock market trends with a dynamic dashboard in Streamlit.
• Utilized the Yahoo Finance API to fetch and process stock data for real-time predictions and visualizations.

Convolutional Neural Network (CNN) Model Development

Tools: TensorFlow, Keras, Python

• Designed and implemented a Convolutional Neural Network (CNN) for [specific application, e.g., image classification, sentiment analysis].
• Optimized model architecture for improved accuracy and efficiency.
• Preprocessed and augmented data to enhance model performance and generalization.
• Utilized Keras for model training, evaluation, and deployment.