▪Text to Code- Developing LLM-based text-to-code models for ServiceNow JavaScript Developers.- Pre-training and fine-tuning(Lora) LLM models.- Building evaluation frameworks and metrics tailored to ServiceNow's text-to-code capabilities.

Leading the @LUUM client engagement for the Machine Learning projects and implemented the solutions for Segmentation, detection and classification problemsData preparation, model design, training and inference pipelines on Nvidia GPU

1.Removing noise from Underwater images using image fusion filtering techniques and detecting the objects under the water using YOLO object detector.2. Segmenation of cloths and groceries from an image using Mask-RCNN and UNET.3. Face recognition of baseball players using Openface,Dlib face embeddings.4.Finding the defects in powerloom yarns by calculating yarn position and orientation .

1. Worked on artificial and natural mango classification using color models.2.Worked on feature extractions on mangoes using SIFT and color models .

Project Name: IntellishelfTools: Dark net,Open CV.Language:Python and C.Description: Application recognize the the brand of a shampoo bottle in a super market shelf.We have implemented it with YOLO algorithm and simple contours.

I am the part of developing the Conversational chat bot and Resume parser using nlp.We have developed a generative model Chat bot using LSTM and tensorflow which is employee friendly chatbot.And we implemented Resume parser which is useful for HR managers.And we are team of 3 members.

I have worked on MHRD project that is Bio Mass Stove can operate with touch screen