Skip to content
View MeetJainAi's full-sized avatar
💭
diving in ml/ai/dl/ds
💭
diving in ml/ai/dl/ds
7 followers · 0 following

Achievements

Achievement: Pull SharkAchievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pull SharkAchievement: YOLOAchievement: Quickdraw

Highlights

  • Pro

Block or report MeetJainAi

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Please don't include any personal information such as legal names or email addresses. Maximum 100 characters, markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
MeetJainAi/README.md 
╔══════════════════════════════════════════════════════════════════╗
║                                                                  ║
║   🌟 Welcome to the intersection of AI, Cloud, and Innovation 🌟  ║
║                                                                  ║
╚══════════════════════════════════════════════════════════════════╝

Typing Animation 1

Typing Animation 2

profile views followers 

mindmap
  root((Meet Shah))
    AI \& ML
      LLMs
      RAG
      MLOps
      Neural Networks
      Deep Learning
      Generative AI
    Cloud
      AWS
      Azure
      GCP
      Oracle
    DevOps
      Terraform
      Docker
      K8s
      CI/CD
      Ansible
      Puppet
      Jenkins
      GitHub Actions
Loading 
class InnovationArchitect:
    def __init__(self):
        self.name = "Meet Shah"
        self.mission = "Bridging AI with Cloud Infrastructure"
        self.superpower = "Turning Coffee into Scalable AI Solutions"
        self.daily_routine = ["Code", "Innovate", "Deploy", "Repeat"]
        
    async def build_future(self):
        while True:
            await self.innovate()
            await self.deploy_to_cloud()
            if self.coffee_level < 50:
                await self.refill_coffee()

# Status: Currently building something awesome...

🔮 Alchemist's Toolkit

🎯 Proven Expertise

  • ✨ Deployed 10+ ML models in production environments
  • ☁️Proficient in major cloud platforms, with a primary focus on AWS (certified), along with experience in Azure and GCP.
  • 📊 Processed and analyzed 500k+ data points
  • 🚀 Maintained 99.5% uptime for critical applications

💡 Areas of Innovation

  • 🧠 Developing large language models for conversational AI
  • 🔄 Automating MLOps pipelines for efficient model deployment
  • 🌐 Architecting multi-cloud solutions for high availability
  • 🛡️ Implementing AI governance and security frameworks

🌐 Certifications & Expertise

AWS ML Engineer Associate Terraform Associate Oracle Generative AI AWS Solutions Architect

🛠️ Alchemist's Workbench

🔥 Essential Skills

🧠 Machine Learning & Deep Learning

  • Proficient in building and deploying machine learning models using frameworks like TensorFlow, PyTorch, and Keras
  • Strong understanding of deep learning architectures such as Convolutional Neural Networks, Recurrent Neural Networks, and Transformers
  • Expertise in natural language processing, computer vision, and other AI/ML applications
  • Experienced in designing and optimizing MLOps pipelines for scalable and efficient model deployment

☁️ Cloud Engineering

  • Skilled in architecting and deploying scalable, highly available, and secure cloud infrastructure on major platforms like AWS, Azure, and GCP
  • Proficient in using Infrastructure as Code tools like Terraform, Ansible, and CloudFormation
  • Experienced in containerization and orchestration with Docker and Kubernetes
  • Adept at designing and implementing CI/CD pipelines for reliable and automated application deployment

🤖 Generative AI

  • Certified in Oracle Generative AI and proficient in building and deploying large language models (LLMs)
  • Experienced in using LLMs for natural language generation, text summarization, and conversational AI applications
  • Skilled in prompting and fine-tuning LLMs for specific use cases
  • Knowledge of ethical and responsible AI practices for generative AI systems

🔧 DevOps

  • Proficient in automating infrastructure provisioning and application deployment using tools like Terraform, Ansible, and Jenkins
  • Experienced in containerization and orchestration with Docker and Kubernetes
  • Skilled in implementing continuous integration and continuous deployment (CI/CD) pipelines
  • Knowledge of monitoring, logging, and incident response for highly available systems

🔥 Forged in the Crucible

🔮 Alchemist's Connections

LinkedIn Twitter Medium Telegram 

╔══════════════════════════════════════════════════════════════════╗
║ "The best way to predict the future is to create it." - Peter F. ║
╚══════════════════════════════════════════════════════════════════╝
github contribution grid snake animation
footer

Pinned Loading

  1. DataScienceIn60Days DataScienceIn60Days Public

    10 7

  2. Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials Public

    Forked from TarrySingh/Artificial-Intelligence-Deep-Learning-Machine-Learning-Tutorials

    A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas …

    Python 3 1

  3. awesome-machine-learning awesome-machine-learning Public

    Forked from josephmisiti/awesome-machine-learning

    A curated list of awesome Machine Learning frameworks, libraries and software.

    Python 2 1

  4. Gender-Classifier-ML-Web-App- Gender-Classifier-ML-Web-App- Public

    Python 2

  5. Iris-Explanatory-Data-Analysis-Web-App Iris-Explanatory-Data-Analysis-Web-App Public

    Python 5

  6. Flask-Simple-TO-DO-Web-App Flask-Simple-TO-DO-Web-App Public

    Python 3