Responsibilities & achievements

• Developed and optimized machine learning models for predictive analytics, including fraud detection and risk assessment. • Designed and implemented computer vision and natural language processing (NLP) projects, improving accuracy and efficiency. • Collected, cleaned, and prepared large datasets for training Machine Learning (ML) and Deep Learning models. • Created and managed data pipelines for model development, including data preprocessing and feature engineering. • Researched and evaluated new AI architectures, techniques, and hyperparameter optimization strategies. • Deployed and monitored ML models on Azure and Heroku, ensuring smooth production integration and performance. • Collaborated with cross-functional teams to integrate AI solutions into business processes and applications.

Responsibilities & achievements

• Led the development of a predictive maintenance system for industrial machinery. • Utilized Python for data preprocessing, feature engineering, and model development, achieving significant improvements in maintenance scheduling and cost reduction.

Responsibilities & achievements

• Led the development and enhancement of AI models for computer vision and NLP tasks, contributing to successful project outcomes. • Engineered data pipelines for model training and deployment, focusing on data quality and processing efficiency. • Conducted research on emerging AI technologies and implemented innovative solutions to improve model performance. • Deployed ML models using Azure and Heroku, managing the entire lifecycle from development to production. • Collaborated with stakeholders to gather requirements and ensure AI solutions met business needs and objectives. • Optimized model hyperparameters and evaluated various architectures to enhance model accuracy and robustness.

Responsibilities & achievements

• Designed and implemented a sports analytics dashboard using Python, Flask, and various data analysis libraries. • Provided insights into player performance and game statistics, leveraging Pandas and Numpy for data manipulation.

Responsibilities & achievements

• Created an end-to-end image classification pipeline using Python and TensorFlow. • Implemented data augmentation techniques and model optimization strategies to achieve high accuracy in real-time image recognition tasks.

Responsibilities & achievements

• Developed a comprehensive personal finance management system in Python, incorporating data visualization with Matplotlib and Seaborn. • Integrated machine learning models for expense prediction and budgeting recommendations.