Suyash Singh

Implemented a Llama2 model from the Hugging face framework, utilized for generating an appropriate tagline for a given image by providing prompt containing the features of the image. Implemented a ClipSeg model from the Hugging face framework, capable of extracting dress from a given image and also utilized Machine Learning techniques to extract colors from dress. Implemented a Product Search engine like Amazon search engine to extract the desired products using Python, Llama2, Pinecone Database, BLIP, Tagging, Langchain, Google Gemini. Implemented Chatbot, which is used to allow user to ask different text query and based on their queries It return the relevant Lookboards of dresses using, Pinecone Database, BLIP, Tagging, Machine Learning, Hugging Face Frameworks, Flask, Langchain, Google Gemini and FastApi.

Designed and implemented a RESTful API utilizing Python and the Django web framework, facilitating CRUD (Create, Read, Update, Delete) operations for a designated resource. Proficiently integrated error handling mechanisms, ensuring graceful responses with suitable status codes and error messages. Defined models such as Post and Comment. Automated the Octro Poker game using Appium and Pytest with Python to ensure high accuracy.

Implemented an Vehicles Detection Model using COCO dataset. With more than 90% accuracy, the Recognition Model was able to assign meaningful captions to the images. Usage of Python libraries such as NLTK, YOLO, Keras, Numpy, Panda and Scikit-learn.