Build News Summary Algorithm1. Improved the performance of the "facebook_bart_large_cnn" summarization model by increasing accuracy from 60% to 88% using Gemma2-2b-it.2. Condensed articles into 85-word summaries using LLMs and advanced prompting techniques like Chain of Thought and Self-Consistency.3. Solved text length limitations by integrating LangChain for handling long documents and deployed the tool using FastAPI.Video Classification Algorithm1.Build a video classification model to categorize video into 10 groups using the supervised learning techniques. Focus on English or non-audio content.2.Filter the non-english content using OpenAI model Whisper and also generate audio transcript. Extract the frames, convert them image to text using MoonDream2 Model.3.Combined the text outputs with metadata of video and applied Llama model with Chain of Thoughts and Self Consistency prompting to refine classification metrics.4.Achieved 85% classification accuracy by leveraging advanced prompting techniques and metadata analysis.

Python,Big Query,Google Cloud Platform,Machine Learning, SQL,