Prashant Singh

Prashant Singh has gained extensive experience in AI and ML through internships and projects. As an AI/ML intern at Sky Trade, he designed custom datasets from large company-provided PDFs using advanced NLP preprocessing and fine-tuned LLMs like DistilGPT, GPT-2, Neo GPT, and LLaMA to develop a personalized chatbot solution. At SaleGully Retail Pvt. Ltd., he worked for over a year, developing an automated social media post generator by integrating Stable Diffusion for high-quality image synthesis and Gemini LLM for dynamic caption generation. His personal projects include an AI-driven age, gender, and sentiment detection model, achieving 93% accuracy in gender classification and 85% in age estimation, significantly improving customer engagement. He also developed an advanced GAN model with a 95% fidelity rate for high-quality synthetic data generation. Additionally, his work in eye disease detection involved designing a hybrid AG-CNN architecture and fine-tuning a Vision Transformer (ViT) for enhanced diagnostic accuracy using retinal imagery. His expertise spans computer vision, deep learning, NLP, and generative models, demonstrating a strong foundation in AI-driven solutions.

Prashant Singh has gained extensive experience in AI and ML through internships and projects. As an AI/ML intern at Sky Trade, he designed custom datasets from large company-provided PDFs using advanced NLP preprocessing and fine-tuned LLMs like DistilGPT, GPT-2, Neo GPT, and LLaMA to develop a personalized chatbot solution. At SaleGully Retail Pvt. Ltd., he worked for over a year, developing an automated social media post generator by integrating Stable Diffusion for high-quality image synthesis and Gemini LLM for dynamic caption generation. His personal projects include an AI-driven age, gender, and sentiment detection model, achieving 93% accuracy in gender classification and 85% in age estimation, significantly improving customer engagement. He also developed an advanced GAN model with a 95% fidelity rate for high-quality synthetic data generation. Additionally, his work in eye disease detection involved designing a hybrid AG-CNN architecture and fine-tuning a Vision Transformer (ViT) for enhanced diagnostic accuracy using retinal imagery. His expertise spans computer vision, deep learning, NLP, and generative models, demonstrating a strong foundation in AI-driven solutions.

B tech from Indian Institute of Information Technology Manipur from Computer Science and Engineering department