Phani Bhattiprolu

Throughout my career, I have successfully navigated the complexities of NLP, Computer Vision (CV), Generative AI/LLM, and Classification and Regression problems. My passion for pushing the boundaries of NLP solutions has been a driving force in my career.

Key Highlights of My Expertise:

NLP Excellence: A significant portion of my experience has been dedicated to NLP, with a focus on solving complex problems using Retrieval Augmented Generative (RAG) pipelines. This includes working with Zero Shot/Few Shot models, showcasing my commitment to staying at the forefront of NLP advancements.

Algorithm Mastery: I have a comprehensive understanding of a diverse range of machine learning algorithms, from Tree-based models and Kernel-based models to statistical machine learning models. This versatility enables me to tailor solutions to the unique challenges presented by each project.

Advanced Model Training: My proficiency extends to training machine learning models using various architectures such as DNN, Embedding Layers, LSTM, RNN, GAN, and Convolution layers, showcasing my commitment to adopting cutting-edge techniques.

Deployment Expertise: I have a proven ability to deploy ML models to production in AWS and Azure using CI/CD pipelines, ensuring that the solutions developed not only meet but exceed operational standards.

Technological Proficiency: Leveraging technologies such as Python 3.X, TensorFlow, PyTorch, Transformers, Scikit Learn, Spacy, Boto3, Open AI, and Llama, I have successfully solved a wide array of machine learning problems.

NLP Solutions in Banking: My experience includes training Question & Answers systems, Text Summarization models, Named Entity Recognition, and Entity resolution systems, demonstrating my adaptability in addressing text-based challenges in the banking domain.

Innovative Frameworks: I have a track record of creating reusable frameworks to train NLP machine learning models on-the-fly, showcasing my commitment to efficiency and scalability in model development.
Object Detection and Layout Models: I have successfully trained Object Detection models using Yolo and Layout detection models using LayoutLM, contributing to efficient data extraction from unstructured documents.
Database Proficiency: Proficient in using SQL Server Databases, Elastic DB, Open Search, and Graph Databases (Neo4J/Amazon Neptune), ensuring seamless integration with diverse data sources.
 

Throughout my career, I have successfully navigated the complexities of NLP, Computer Vision (CV), Generative AI/LLM, and Classification and Regression problems. My passion for pushing the boundaries of NLP solutions has been a driving force in my career.

Key Highlights of My Expertise:

NLP Excellence: A significant portion of my experience has been dedicated to NLP, with a focus on solving complex problems using Retrieval Augmented Generative (RAG) pipelines. This includes working with Zero Shot/Few Shot models, showcasing my commitment to staying at the forefront of NLP advancements.

Algorithm Mastery: I have a comprehensive understanding of a diverse range of machine learning algorithms, from Tree-based models and Kernel-based models to statistical machine learning models. This versatility enables me to tailor solutions to the unique challenges presented by each project.

Advanced Model Training: My proficiency extends to training machine learning models using various architectures such as DNN, Embedding Layers, LSTM, RNN, GAN, and Convolution layers, showcasing my commitment to adopting cutting-edge techniques.

Deployment Expertise: I have a proven ability to deploy ML models to production in AWS and Azure using CI/CD pipelines, ensuring that the solutions developed not only meet but exceed operational standards.

Technological Proficiency: Leveraging technologies such as Python 3.X, TensorFlow, PyTorch, Transformers, Scikit Learn, Spacy, Boto3, Open AI, and Llama, I have successfully solved a wide array of machine learning problems.

NLP Solutions in Banking: My experience includes training Question & Answers systems, Text Summarization models, Named Entity Recognition, and Entity resolution systems, demonstrating my adaptability in addressing text-based challenges in the banking domain.

Innovative Frameworks: I have a track record of creating reusable frameworks to train NLP machine learning models on-the-fly, showcasing my commitment to efficiency and scalability in model development.
Object Detection and Layout Models: I have successfully trained Object Detection models using Yolo and Layout detection models using LayoutLM, contributing to efficient data extraction from unstructured documents.
Database Proficiency: Proficient in using SQL Server Databases, Elastic DB, Open Search, and Graph Databases (Neo4J/Amazon Neptune), ensuring seamless integration with diverse data sources.
 

Bachelors in Computer Science