GOPI CHAND PENDYALA

Image Super-Resolution using Generative Adversarial Network (GAN)

• Engineered and deployed an advanced Image Super-Resolution model leveraging Generative Adversarial Networks (GAN), Python, and TensorFlow, overcoming the complexities of neural network configurations and achieving a pivotal KPI of 4x image resolution enhancement.
• Utilized state-of-the-art Artificial Intelligence and Deep Learning methodologies to optimize the performance and robustness of a multifaceted neural network model, addressing challenging computational and time management requirements.

Cricket Match Score Prediction

• Developed a predictive model for cricket match scores, achieving a notable 91% accuracy rate using R programming and advanced machine learning techniques, specifically the k-Nearest Neighbors algorithm.
• Executed extensive Data Scraping and Data Preprocessing to curate a robust dataset from diverse online sources, followed by intricate Feature Engineering that transformed 20+ raw data attributes into 3 highly effective features.

• Awarded inaugural ’Innovation Catalyst’ by Franklin Templeton firm in challenging current status quo

• Attained ’Certified Disciplined Agilist’ certification from Disciplined Agile Development consortium