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Akashpaul2030/README.md

πŸ‘¨β€πŸ’» Pritidhrita Paul Akash

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πŸš€ About Me

Machine Learning Engineer specializing in Generative AI and Large Language Models

I design and implement innovative ML solutions with a focus on LLM fine-tuning, federated learning, and scalable AI architectures. Currently working at DevolvedAI (LA), where I engineer comprehensive workflows for Llama 3.1 models and build evaluation pipelines across multiple domains.

  • πŸ”­ Working on Federated Learning for Privacy-Preserving LLM Fine-tuning
  • 🌱 Researching AI Content's Impact on Mental Wellbeing
  • πŸ’¬ Ask me about LLMs, RAG Systems, LoRA Fine-tuning, Distributed ML
  • πŸ“« Reach me at: akashpaul2030@gmail.com
Akash's GitHub stats GitHub Streak

πŸ’» Tech Stack

Category Technologies
Languages Python JavaScript C SQL
LLM & AI PyTorch TensorFlow Hugging Face LangChain OpenAI
Big Data PySpark Ray Dask Hadoop Kafka
Databases ChromaDB MySQL MongoDB
DevOps & Cloud AWS Azure Docker Nginx

πŸ† Projects & Research

Featured Projects

Research Pilot

Research Pilot

LangGraph, OpenAI (GPT-4), Pydantic, scholarly - A Research Paper Analysis Agent that automates literature search, analysis, and insight extraction

Synthetic Data Generation

Synthetic Data

LlamaIndex, OpenAI, FAISS - Generated 10,000+ synthetic Q&A pairs with vector database integration for efficient retrieval and augmentation

Research Areas

Federated Learning for LLM Fine-tuning

Federated Learning

Ray, PyTorch, Transformers, PEFT, LoRA

Implemented privacy-preserving federated learning architecture for Llama 3.1 fine-tuning with distributed evaluation pipelines

Mental Health for LLMs

Mental Health

Sentiment Analysis, Content Moderation APIs

Researched impact of AI content on user mental wellbeing and developed content filtering systems to detect harmful outputs

🌐 Connect With Me


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  1. First-ML-Project-Iris-Dataset-Bigineers First-ML-Project-Iris-Dataset-Bigineers Public

    I use EDA to more explore and apply 7 different classifiers for iris_datset

    Jupyter Notebook 1

  2. Habermans_model_EDA-_Model Habermans_model_EDA-_Model Public

    The dataset contains the survival of patients who had undergone surgery for breast cancer.

    Jupyter Notebook

  3. Restaurant-sentiment-analysis-NLP Restaurant-sentiment-analysis-NLP Public

    The purpose of this analysis is to build a prediction model to predict whether a review on the restaurant is positive or negative or neutral.

    Jupyter Notebook

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