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Hi there šŸ‘‹

I'm Srikanth Machiraju an Architect at Microsoft, Published Author and Independent Researcher. I'm currently learning distributed machine learning and Artificial intelligence. I create a blend of my expertise in building cloud-native solutions with AI / ML to create innovative products. I also write articles on linked-in and towards datascience related to building intelligent apps for cloud and ML. I'm specialized in Large language models, deep reinforcement learning, so if you are looking for tips, quick help or have an interesting project you can always reach out to me.

Here are some of the books I authored.

šŸ“« How to reach me: Write to [email protected]

šŸ‘Æ Iā€™m looking to collaborate on research work related to reinforcement learning.

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

sriksmachi/sriksmachi is a āœØ distributed ML systems āœØ repository where you can find all my work.

Here are some ideas to get you started:

  • šŸ”­ Iā€™m currently working on applied RL
  • šŸŒ± Iā€™m currently learning distributed ML systems
  • šŸ‘Æ Iā€™m looking to collaborate on RL in the field of industrial automation
  • šŸ¤” Iā€™m looking for help with ...
  • šŸ’¬ Ask me about ML/DS/AI, designing distributed systems for the cloud, microservices design
  • šŸ“« How to reach me: [email protected] / linked-in

Notebooks

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Classical ML

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Anomaly detection using PCA https://github.com/sriksmachi/sriksml/blob/main/pca.ipynb
Resampling Approaches https://github.com/sriksmachi/sriksml/blob/main/ResamplingApproaches.ipynb

Language Models

Text generation using Simple RNN and Glove Models https://github.com/sriksmachi/sriksml/blob/main/language-models/rnn-glove-embeddings.ipynb
Build a transformer from scratch https://github.com/sriksmachi/sriksml/blob/main/genai/transformers_101_nmt_eng_hin.ipynb

Generative AI

Variational Auto Encoders https://github.com/sriksmachi/sriksml/blob/main/genai/variational-auto-encoders.ipynb
Cycle GANs https://github.com/sriksmachi/aimriscan

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Large Language Models

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Building an Azure Quiz using GPT, Chat GPT, and Embeddings models https://github.com/sriksmachi/openai-samples/tree/main/azure-quiz
Document classification by fine-tuning Open AI Models https://github.com/sriksmachi/openai-samples/tree/main/document-classification
Prompt engineering samples https://github.com/sriksmachi/openai-samples/tree/main/prompt-engineering
Build AI Apps using langchain, vector databases, embeddings https://github.com/sriksmachi/openai-samples/tree/main/complete-ai-app
Knowledge distillation in large language models https://github.com/sriksmachi/sriksml/blob/main/language-models/knowledge_distillation_llm.ipynb
Fine-tuning LLMs using RLHF https://github.com/sriksmachi/sriksml/blob/main/language-models/fine_tuning_llms_rlhf.ipynb

==============================================

Reinforcement Learning

==============================================

Q-learning TBD
REINFORCE https://github.com/sriksmachi/sriksml/blob/main/reinforcement-learning/reinforce.ipynb
SARSA TBD
DQN TBD
DDPG TBD
TRPO TBD
PPO https://github.com/sriksmachi/sriksml/blob/main/reinforcement-learning/ppo.ipynb

Projects

Ishara https://github.com/sriksmachi/ishara
Octopus https://github.com/sriksmachi/ishara
SuperCabs https://github.com/sriksmachi/supercabs
RBEI https://github.com/sriksmachi/rbei

Srikanth Machiraju's Projects

melanoma_cancer_detection_using_neural_networks icon melanoma_cancer_detection_using_neural_networks

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 is WIP - stay tuned

mycode icon mycode

Code Samples for Sharing with Public

octopus icon octopus

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

rbei icon rbei

A Hackathon Project for Robert Bosch Engineering and Business Solutions

supercabs icon supercabs

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.

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