NLP Engineer working on the development of applications using Large Language Models (LLMs).I have recently worked on many generative AI projects like QA over thousands of documents and interaction with databases in natural language. I have experience with OpenAI GPT 4, chat GPT GCP Palm 2 and embeddings models. I am familiar with RAG-based systems and Various Vector Databases.I have Solid understanding of maths behind machine learning algorithms. Have worked on deep learning projects including Natural language Processing, Computer Vision, Time Series and Recommender Systems. I also have exposure to big data and Cloud Computing platforms like GCP , Azure and AWS.Evaluation of Few-Shot Prompting and Evaluation of LLMs using EleutherAI's Models.Conducted a comprehensive assessment of generative performance across three prominent language models: OPT, GPTNeo, and Dolly.Utilized benchmark datasets including AI2’s Reasoning Challenge, Adversarial Natural Language Inference, and Winograd Schema Challenge.Employed diverse prompt settings such as Zero-Shot, One-Shot, Three-Shot, and Five-Shot prompts to evaluate model efficacy.Identified a direct correlation between model size and performance across all benchmarks.Noted a substantial performance boost with an increase in the number of few-shot (in-context) examples in the prompt, indicating the effectiveness of this approach in enhancing model capabilities.Technical Data Skills:- Machine Learning, Deep Learning, Data Analytics, Natural Language Processing, Exploratory Data Analytics, Data Visualization, Data engineering, Statistical Modeling, Data Mining, StatisticsProgramming Language:- Python, SQLData tools: MySQL, Power BI, Tableau, Jupyter Notebooks, PyCharm, Gitlab, VS code, Docker, CI/CD, Git, ETLMachine Learning Models:- Linear Regression, Logistic Regression, KNN, K Means, SVM, Decision Tree, Random Forest, Naïve Bayes, Xgboost, AWS Lambda, Amazon S3, Sagemaker, ML Model Deployment & Monitoring(MLOps)Python Libraries:- Pandas, Numpy, Scikit-learn, NLTK, Matplotlib, Seaborn, Wordcloud, Spacy, TensorFlow, PySparkDeep Learning:- ANN, CNN, RNN, LSTM, Autoencoders, ResNet, GAN, Transformers, Prompt Engineering Transfer Learning, OpenCV, Feature extraction, Image analysis, Solid understanding of linear algebra, image processingGenerative AI:- GPT-3, GPT4, OpenAI, LLMs, RAGs, BERT, Gemini Pro, Llama, Langchain, Vector databases, FastAPINLP:- NLTK, Spacy, Hugging Face TransformersOpen to interesting conversations and collaboration.𝐄𝐦𝐚𝐢𝐥: somanathtk198@gmail.com