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kilickursat/README.md
  • 👋 Hi, I’m @kilickursat
  • 👀 I’m interested in artificial intelligence applications for tunnel boring machine (TBM).
  • 🌱 I’m currently implementing supervised and unsupervised learning models for the TBM cutter wear prediction and lithology identification.
  • 💞️ I’m looking to collaborate on for the next research about Auto TBM advancement.
  • 📫 How to reach me ; [email protected]

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  1. 30days 30days Public

    Forked from streamlit/30days

    #30DaysOfStreamlit is a 30-day social challenge for you to build and deploy Streamlit apps.

    Python

  2. Accelerometer-Data-Exploration Accelerometer-Data-Exploration Public

    Exploratory analysis of Apple watch and accelerometry data; including the evaluation of a Physical activity intervention using the boris bike trips data in R.

  3. Clustering-guided-LightGBM Clustering-guided-LightGBM Public

    Soft ground tunnel lithology classification using clustering-guided light gradient boosting machine

    Jupyter Notebook

  4. Data-Science--Cheat-Sheet Data-Science--Cheat-Sheet Public

    Forked from faaltunel/Data-Science--Cheat-Sheet

    Cheat Sheets

    TeX

  5. Exploratory_Data_Analysis_using_Python_Library Exploratory_Data_Analysis_using_Python_Library Public

    Forked from amitjain2110/Exploratory_Data_Analysis_using_Python_Library

    Libaries : dtale , pandas_profiling , sweetviz, pandas_visual_analysis

    Jupyter Notebook

  6. lithology-classifier lithology-classifier Public

    Python