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sriksmachi/README.md

๐Ÿ‘‹ Hello World! I'm Srikanth Machiraju

๐ŸŽฏ AI Architect @ Microsoft | ๐Ÿ“š Published Author | ๐Ÿ”ฌ Independent Researcher

"Bridging the gap between cutting-edge AI research and real-world applications through innovative cloud-native solutions"

I'm passionate about building the next generation of intelligent systems that transform industries. My expertise spans Large Language Models, Deep Reinforcement Learning, and Distributed ML Systems. I architect scalable AI solutions on the cloud while contributing to the AI community through research, writing, and open-source projects.

๐Ÿค– What I Do

  • ๐Ÿ—๏ธ Architect AI Solutions at scale for enterprise applications
  • ๐Ÿ“ Write Technical Content on LinkedIn and Medium
  • ๐Ÿ”ฌ Research in Reinforcement Learning and Industrial Automation
  • ๐ŸŒŸ Mentor developers building intelligent applications

๐Ÿ“š Published Author - Books That Inspire Innovation

Sharing knowledge through comprehensive guides on AI and cloud technologies

๐Ÿ“ซ How to reach me: Write to vishwanath.srikanth@mail.com / ping me on linked-in

๐Ÿ‘ฏ Iโ€™m looking to collaborate on research work related to reinforcement learning.

โšก Fun fact: I'm actually not as busy as it appears :)

sriksmachi/sriksmachi is a โœจ AI/ML โœจ repository where you can find all my work.

Here are some ideas to get you started:

  • ๐Ÿ”ญ Iโ€™m currently working on applied RL
  • ๐ŸŒฑ Iโ€™m currently learning distributed ML systems
  • ๐Ÿ‘ฏ Iโ€™m looking to collaborate on RL in the field of industrial automation
  • ๐Ÿค” Iโ€™m looking for help with ...
  • ๐Ÿ’ฌ Ask me about ML/DS/AI, designing distributed systems for the cloud, microservices design

๐Ÿ—๏ธ My Work Portfolio

"Where AI Architecture meets Practical Innovation"

The sriksmachi repository is a โœจ comprehensive AI/ML knowledge hub โœจ showcasing production-ready solutions, research implementations, and educational resources. Each section below contains battle-tested examples, interactive notebooks, and mini-projects applicable across industries.

๐ŸŽฏ Core AI/ML Domains

๐Ÿ”ฅ Domain ๐Ÿš€ Repository ๐Ÿ“Š Focus Area
๐ŸŒ Azure ML Explore โ†’ Cloud-native ML solutions
๐Ÿง  Large Language Models Explore โ†’ LLM applications & fine-tuning
๐Ÿ“ˆ Classical Machine Learning Explore โ†’ Traditional ML algorithms
๐ŸŽจ Generative AI (non-LLM) Explore โ†’ Creative AI solutions
๐ŸŽฎ Reinforcement Learning Explore โ†’ RL research & applications

๐ŸŒŸ Featured Projects

Real-world applications showcasing AI innovation in action

๐Ÿš€ Project ๐Ÿ”— Repository ๐Ÿ’ก Innovation
๐Ÿคฒ Ishara View Project โ†’ Gesture recognition system
๐Ÿ™ Octopus View Project โ†’ Multi-modal AI platform
๐Ÿš• SuperCabs View Project โ†’ Smart transportation solution
๐Ÿข RBEI View Project โ†’ Enterprise AI framework

๐Ÿ“Š GitHub Analytics

GitHub Stats

Top Languages


๐Ÿ› ๏ธ Tech Stack & Expertise

๐Ÿค– AI/ML Technologies

Python TensorFlow PyTorch Scikit Learn

โ˜๏ธ Cloud & DevOps

Azure Docker Kubernetes

๐Ÿ’ป Programming & Tools

C# JavaScript Git


๐ŸŒŸ "Innovation happens when AI meets real-world challenges"

โญ Star my repositories if you find them useful!
๐Ÿค Let's build the future of AI together!

Wave

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  1. sriksml sriksml Public

    Welcome to SriksML โ€“ a comprehensive repository of hands-on, production-inspired Jupyter notebooks and code samples for modern machine learning, deep learning, and AI workflows.

    Jupyter Notebook 7 1

  2. ishara ishara Public

    Gesture Detection using Deep Learning techniques, this repository contains code for detecting gesture from a sequence of frames created from a 2-sec video (15 fps) using deep learning techniques liโ€ฆ

    Jupyter Notebook 2

  3. melanoma_cancer_detection_using_neural_networks melanoma_cancer_detection_using_neural_networks Public

    This repository contains code artifacts which explain how to operationalize deep neural network models on Azure ML using MLFLow. The problem domain we will focus on is to detect skin cancer. This iโ€ฆ

    Jupyter Notebook

  4. octopus octopus Public

    This project explains how to move from a Jupyter notebook phase to a production ready training script that can run in a distributed training mode using Azure ML, Horovod and TF

    Jupyter Notebook 2

  5. supercabs supercabs Public

    Sample for training an agent which mimics a cab driver to gain maximum profits by picking the correct rides. The agent is trained using deep Q-learning training techniques.

    Jupyter Notebook 10 2

  6. aimriscan aimriscan Public

    An AI method to generate MRI scans of brain images using GANs

    Jupyter Notebook 1