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kashyaparun25/README.md

👋 Arun Kashyap

Senior AI Engineer • Data Scientist • AI Consultant

Building intelligent systems that scale

LinkedIn Email Portfolio

🎯 Core Expertise

AI Engineering → RAG Systems → LLM Integration → Agent Development
Cloud Architecture → Microservices → DevOps → Infrastructure as Code
Full-Stack Development → System Design → Real-time Applications → API Development
Data Science → ML Pipelines → Analytics → Visualization

🚀 Technical Arsenal

🤖 AI & Machine Learning

LLM Integration:
  - OpenAI GPT-4, Claude, Gemini
  - Custom fine-tuning & optimization
  - Prompt engineering & chain design

RAG Systems:
  - Vector databases (Pinecone, Chroma)
  - Semantic search & retrieval
  - Context-aware AI applications

ML Engineering:
  - TensorFlow, PyTorch, Scikit-learn
  - Model deployment & MLOps
  - Computer vision & NLP

☁️ Cloud & DevOps

Cloud Platforms:
  - AWS, GCP, Azure
  - Serverless architectures
  - Multi-cloud strategies

Infrastructure:
  - Docker & Kubernetes
  - Terraform, CloudFormation
  - CI/CD pipelines (GitHub Actions)

Monitoring:
  - Logging, metrics, alerts
  - Performance optimization
  - Cost management

💻 Full-Stack Development

Frontend:
  - React 19, Next.js 15, TypeScript
  - Three.js, WebGL
  - Responsive & accessible design

Backend:
  - Python (FastAPI), Node.js
  - RESTful APIs, GraphQL
  - Microservices architecture

Database:
  - PostgreSQL, MongoDB, Redis
  - Query optimization
  - Data modeling & migrations

📊 Data Engineering

Data Processing:
  - Pandas, NumPy, PySpark
  - ETL pipelines
  - Big data processing (Hadoop)

Analytics:
  - Statistical modeling
  - Data visualization
  - Business intelligence

Databases:
  - SQL optimization
  - NoSQL patterns
  - Real-time data streaming

💼 What I Build

🤖 AI Applications

Conversational AI systems with RAG
Multi-agent orchestration
Real-time voice processing
Custom LLM integrations

Impact: <2s response times
99.9% uptime • 1000+ concurrent users

🏗️ System Architecture

Scalable microservices
Cloud-native applications
Event-driven systems
High-performance APIs

Impact: 50% cost reduction
10x performance • Auto-scaling

📊 Data Solutions

ML pipelines & MLOps
Analytics platforms
Real-time dashboards
Predictive models

Impact: 95% accuracy
Real-time insights • Automation

🎯 Specialized Skills
RAG System Design AI Agent Development Prompt Engineering
System Architecture Cloud Optimization API Development
Real-time Systems Database Design Performance Tuning
DevOps Automation Security Implementation UX/UI Design

📈 GitHub Activity

🏆 Key Achievements

+ Built AI platforms serving 10,000+ concurrent users
+ Architected cloud systems with 99.99% availability
+ Reduced infrastructure costs by 40% through optimization
+ Deployed ML models with 95%+ prediction accuracy
+ Automated CI/CD reducing deployment time by 90%

🛠️ Development Philosophy

Clean Architecture • Scalable Design • Performance First
Test-Driven • Security-Focused • User-Centric

📫 Let's Collaborate

Open to opportunities in:
AI Engineering • Cloud Architecture • Technical Leadership • Innovation Projects

LinkedIn Email

"Engineering intelligent systems that drive real-world impact" ⚡

Profile Views

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  1. ResNet50-Unleashed-Mastering-CIFAR-10-Image-Recognition ResNet50-Unleashed-Mastering-CIFAR-10-Image-Recognition Public

    "ResNet50 Unleashed: Mastering CIFAR-10 Image Recognition" is a deep learning project focused on benchmarking the ResNet50 architecture against traditional neural networks and CNNs using the CIFAR-…

    Jupyter Notebook

  2. AI-Powered-Health-Monitoring-Chatbot AI-Powered-Health-Monitoring-Chatbot Public

    Python 1

  3. Decision-Tree-Analysis-Titanic-Dataset Decision-Tree-Analysis-Titanic-Dataset Public

    Build and evaluate a decision tree using the Titanic dataset, including tree pruning through cross-validation, accuracy assessment, and comparison with a Random Forest model.

    Jupyter Notebook

  4. Implementing-K-Means-Clustering-on-2D-and-MNIST-Data Implementing-K-Means-Clustering-on-2D-and-MNIST-Data Public

    Explore K-means clustering on 2D and MNIST datasets. Includes generating and visualizing 2D data, implementing the K-means algorithm, Mini-Batch K-means training, and evaluating performance using i…

    Jupyter Notebook

  5. Mental-Health-Chatbot-using-RoBERTa-and-Gemini Mental-Health-Chatbot-using-RoBERTa-and-Gemini Public

    Jupyter Notebook 2

  6. portfolio portfolio Public

    Arun Kashyap's Portfolio

    Python