MANAV RAVAL

Trained and deployed diverse ML models (supervised, unsupervised, RL) and CNN/ANN architectures using TensorFlow and Keras, enhancing predictive capabilities.

Designed and implemented Power BI dashboards with DAX for KPI tracking, performing comprehensive EDA and data cleaning on complex real-world datasets.

Explored and applied Generative AI, Microsoft Copilot, and Azure cloud fundamentals to develop innovative AI solutions.

Delivered a capstone project, integrating AI and Azure services to solve a real-world problem from conception to deployment.

Organized successful technical events, including a Git & GitHub workshop, engaging over 100 student attendees.

Coordinated seamlessly across design, logistics, and speaker teams to ensure flawless event execution.

Drove community initiatives that expanded the campus developer network and actively promoted peer learning opportunities.

Built and rigorously evaluated ML models, achieving approximately 92% prediction accuracy on benchmark datasets.

Engineered efficient feature extraction and preprocessing pipelines, significantly improving overall model performance and reliability.

Applied a range of classification and regression algorithms in Python/Scikit-learn, meticulously evaluating models using precision, recall, and F1-score metrics.

Developed and optimized ML models on real-world datasets, enhancing accuracy through advanced feature engineering and optimization techniques.

Performed extensive EDA and data visualization to extract actionable insights from complex structured datasets, informing strategic decisions.

Designed and developed an AI-powered healthcare recommendation platform utilizing Google AI tools, improving patient care suggestions.