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avi350751/Readme.md

👋 Hi there, I’m Avishek!

I’m a Senior Automation Engineer with a strong focus on building scalable, efficient, and intelligent testing solutions. I specialize in automation strategy, tool evaluation, and AI test coverage optimization, with hands-on expertise across:

🧪 UI Automation ☁️ Salesforce Automation 🔌 API Automation 🎓 AI Testing

I hold a Postgraduate Diploma in Artificial Intelligence & Machine Learning from the Texas McCombs School of Business. A lifelong learner, I actively explore AI systems, LLMs, and agentic architectures, bridging theory with real-world engineering use cases.

💡 What Drives Me :

  • Solving data-driven and system-level problems
  • Applying scientific reasoning to engineering decisions
  • Exploring how AI can augment software testing and quality engineering
  • Building practical, production-ready Agentic AI workflows

🚀 What You’ll Find Here

On this GitHub, you’ll find projects and experiments around:

🤖 Automation frameworks & testing utilities 🧠 Machine Learning & Generative AI concepts 🕸️ Agentic AI, LLM evaluation, and tool-driven agents ⚙️ CI/CD, test strategy, and AI-assisted quality engineering

I enjoy collaborating, sharing learnings, and building things that are simple, robust, and impactful.

📊 GitHub at a Glance

🤝 Let’s Connect

If you’re interested in automation, AI-driven testing, agentic systems, or GenAI engineering, feel free to connect or collaborate. Always happy to exchange ideas and learn together.

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  1. boston_house_pricing boston_house_pricing Public

    This Boston house-price data is used here to address regression problems.

    Jupyter Notebook

  2. EDA EDA Public

    Exploratory data analysis on different Kaggle datasets

    Jupyter Notebook

  3. car_prediction car_prediction Public

    This dataset contains information about used cars.

    Jupyter Notebook

  4. ml-pipeline-demo ml-pipeline-demo Public

    Python

  5. auto-tester-repo1 auto-tester-repo1 Public

  6. intro-to-streamlit intro-to-streamlit Public

    Introduction to Streamlit

    Python