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Karimkhab/README.md
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Khabirakhmanov Karim

About

Applied AI student (Innopolis University, GPA 4.89). Build ML systems and LLM-based pipelines end-to-end.


Experience

  • Build ML pipelines: parsing → features → modeling → inference
  • Develop LLM systems: agents, tool-calling, RAG
  • Design distributed services (API, workers, queues)
  • Train and fine-tune models (CatBoost, CNN, LoRA / QLoRA)
  • Prepare datasets and evaluation pipelines.

Tech Stack

Achievements

  • ML Intern — Yandex
  • 1st place — T-Bank Code & Sport (2026)
  • Hackathon participant — Telegram Ads Forecasting

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Pinned Loading

  1. programming-in-python programming-in-python Public

    Educational Repository for Python programming

    Jupyter Notebook 1

  2. med-app-tele-medicine med-app-tele-medicine Public

    My summer project from GitLab. Telegram Bot + Mini App

    Python

  3. telegram-ads-forecaster telegram-ads-forecaster Public

    REST API for predicting ad views in Telegram.

    Jupyter Notebook

  4. shamir-secret-dnp shamir-secret-dnp Public

    Project to create a distributed application for the Shamir Algorithm

    Python 1

  5. log-copilot-bpmsoft log-copilot-bpmsoft Public

    LogCopilot for BPMSoft - AI-log analysis, incident summary, and ticket design

    Python 1 1

  6. robust-ml-pipelines-iml26 robust-ml-pipelines-iml26 Public

    Robust ML pipelines for image classification, tabular modeling, and anomaly detection (IML26 assignment, 98.7/100)

    Jupyter Notebook