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Gdahuks/README.md

Hubert Książek Linkedin Github

R&D Engineer at Dataedo | Mathematician & Data Scientist

⚙️ Tech Stack

Python PyTorch TensorFlow XGBoost OpenCV scikit-learn NumPy SciPy SymPy Pandas Polars Statsmodels Seaborn Matplotlib Plotly Streamlit FastAPI Beautiful Soup LangChain LangSmith Anaconda SageMath

CSharp dotNet LINQ WinForms DevExpress ANTLR

Docker Linux Git GitHub Gitlab Gitlab CI/CD -.pre-commit Postman DBeaver REST APIs JDBC ODBC ADO.NET

Snowflake SQL Server PostgreSQL MySQL Google BigQuery SQLite

R dplyr ggplot2 tidyr emmeans caret LaTeX Overleaf

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  1. Image_contrast_enhancement Image_contrast_enhancement Public

    ImageContrastEnhancement is a demonstration of the capabilities of convolutional genetic algorithms in image processing, specifically in the area of contrast enhancement.

    Jupyter Notebook 1

  2. Road_Detection_via_U-NET Road_Detection_via_U-NET Public

    Automatic Road Detection via U-NET Neural Network. The project focuses primarily on implementing the U-NET architecture so that it can be easily modified by changing individual parameters.

    Python 1

  3. pre-commit pre-commit Public

    Prezentacja zastosowania narzędzi do statycznej analizy kodu wraz z ich automatyzacją przy pomocy pre-commit, oraz pipeline. Prezentacja przygotowana na potrzeby przedmiotu "Programowanie zorientow…

    Python 2

  4. housing_price_prediction housing_price_prediction Public

    House pricing prediction ML pipeline. Scrapes data, stores in Azure, uses ML models, and provides API. Built with Python, FastAPI, Azure, and Docker for seamless deployment and scalability.

    Python

  5. Calculates the stationary state for ... Calculates the stationary state for the given transition matrix by solving an eigenproblem.
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    import numpy as np
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    import scipy
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    def calculate_stationary_state(transition_matrix: np.ndarray) -> np.ndarray:
  6. Calculates the transition matrix fro... Calculates the transition matrix from a given 1D numpy array.
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    import numpy as np
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    def get_valid_indices(series: np.ndarray) -> (np.ndarray, np.ndarray):
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        """