class SparshJoshi:
def __init__(self):
self.name = "Sparsh Joshi"
self.institute = "IIT"
self.roles = ["BTech @ IIT Mandi", "ML Enthusiast", "GenAI Builder", "Open Source Contributor"]
self.research = ["Computer Vision", "NLP", "Generative AI", "MLOps"]
self.building = ["RAG Pipelines", "Fine-tuned LLMs", "CV Systems", "AI Agents"]
self.frameworks = ["PyTorch", "TensorFlow", "HuggingFace", "LangChain"]
self.philosophy = "Bridge the gap between research papers and production systems"
self.fun_fact = "I read arxiv papers the way others read the news 📄"
def say_hi(self):
print("Thanks for stopping by! Let's push the frontier together 🚀")
me = SparshJoshi()
me.say_hi()| 🧠 | Deep interest in LLMs, RAG, Diffusion Models and Agentic AI |
| 🔬 | Working on Computer Vision and NLP — from research to deployment |
| 🤗 | Active with HuggingFace, open-source tools and the broader ML community |
| 📐 | Obsessed with MLOps — clean pipelines, reproducible experiments, tracked metrics |
| 📄 | Love reading and implementing research papers — from arxiv to working code |
| 📫 | Reach me on LinkedIn |
🧠 ML / DL / GenAI
⚙️ Backend, APIs & Infra
| 🔭 Domain | 🛠️ What I Work On |
|---|---|
| Generative AI | LLM fine-tuning, RAG pipelines, prompt engineering, AI agents |
| Computer Vision | Object detection, segmentation, image classification, OpenCV |
| NLP | Text classification, transformers, embeddings, semantic search |
| MLOps | Experiment tracking (MLflow), model serving, CI/CD for ML |
| Deep Learning | CNNs, RNNs, Transformers, GANs, Diffusion Models |
