class PranayTej:
name = "Lakshmi Pranay Tej Ravulakol"
role = ["AI/ML Developer", "Full-Stack Builder", "AI Innovator"]
languages = ["Python ", "JavaScript ", "SQL "]
interests = [
"Large Language Models & Fine-tuning ",
"Computer Vision & Object Detection ",
"Generative AI — GANs & Diffusion Models ",
"End-to-End ML Pipelines & Deployment ",
"Building AI-Powered Full-Stack Products ",
"ML Theory — Linear Algebra, Probability, Optimization ",
]
currently = "Training models & shipping products "
fun_fact = "I debug faster than I find my charger "
def say_hi(self):
print("Let's build something that actually works. ")🤖 AI/ML Frameworks
🧩 ML Concepts
Supervised Learning Transfer Learning Neural Networks NLP Computer Vision GANs Object Detection Deep Learning Generative AI Regression Classification Clustering SVM Decision Trees Random Forests
⚙️ ML Workflow
Model Training Hyperparameter Tuning Cross-Validation Data Augmentation Dropout Batch Normalization Regularization Embedding Optimization Feature Engineering
📐 Foundations
Linear Algebra Probability Statistics Data Structures Algorithms
🚀 Backend & Deployment
🎨 Frontend
💻 Languages
📊 Data & Visualization
| Area | What I'm Into |
|---|---|
| 🧠 NLP | Fine-tuning Transformers, BERT, legal & domain-specific LLMs |
| 👁️ Computer Vision | Object Detection, GANs, real-time inference pipelines |
| 🎨 Generative AI | GANs, Diffusion Models, style transfer, image synthesis |
| ⚙️ MLOps | End-to-end pipelines, Docker, FastAPI deployment |
| 🌐 AI Products | Full-stack apps powered by real ML models |
| 📐 ML Theory | Optimization, probability, linear algebra deep dives |
| 🔬 Area | 📚 What I'm Diving Into |
|---|---|
| 🤖 LLMs | Fine-tuning & prompt engineering on domain-specific data |
| 🎨 Generative AI | Diffusion Models, Stable Diffusion, image synthesis |
| ⚙️ MLOps | Model versioning, CI/CD pipelines, scalable inference |
| 📐 ML Theory | Advanced optimization, Bayesian methods, probabilistic ML |
