📘 AI/ML Engineer | NLP & LLMs | Scaling Laws Enthusiast —

🙏 Hello, I’m Nidhi

I’m a machine learning enthusiast focused on NLP, LLMs, and AGI research.
This portfolio showcases my deep learning projects and reproducible research. My work revolves around:

  • 🔬 Exploring and reproducing scaling laws in deep learning
  • 🧠 Building transformer architectures from scratch
  • ⚙️ Fine-tuning LLMs for domain-specific applications
  • 📈 Conducting empirical research to understand model behaviors

🧠 Featured Projects

🔹 LLM Journey

A curated journey through large language model papers and experiments — combining paper reading, conceptual reflections, and reproducible notebooks.

🔹 DeepLearning_Projects

This repository showcases a collection of hands-on deep learning projects I’ve worked on, covering key areas such as image classification (CNNs). The projects reflect my understanding of foundational architectures (like Feedforward, CNN, RNN, and Transformers) and includes PyTorch implementations, experiments, and model evaluations.

🔹 Scaling Laws Reproduction

Reproduced key findings from seminal papers like Kaplan and Chinchilla, analyzing loss vs. compute trade-offs with synthetic datasets. 💡 Insights: Empirical curve fitting, plotting, scaling analysis.

🔹 MachineLearning Business Projects

This repository contains real-world, business-focused machine learning projects that demonstrate my ability to solve practical problems using data-driven approaches. These projects highlight my experience in applying ML to deliver measurable business value—such as increasing revenue and improving product targeting—using tools like scikit-learn, pandas, SQL.

📘 Blog & Notes

📫 Contact