Comprehensive Guide to Geospatial Analysis, Machine Learning, and Data Processing in Python - Part 4

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  • Опубліковано 7 вер 2024
  • Welcome to our comprehensive guide on geospatial analysis, machine learning, and data processing using Python! In this tutorial, we cover a wide range of topics, providing you with practical examples and detailed explanations for each section. Whether you're a beginner or an experienced data scientist, this tutorial has something for everyone.
    Topics Covered:
    Data Normalization and Feature Extraction
    Applying K-means Clustering
    Random Forest Classifier
    Building a CNN with Keras
    ARIMA Model for Time Series Forecasting
    Anomaly Detection with Isolation Forest
    Geospatial Data Manipulation with GeoPandas and Folium
    Geospatial Clustering with K-means
    Spatial Join with GeoPandas
    Kriging Interpolation
    Time-Series Geospatial Data Visualization
    Digital Elevation Model (DEM) Visualization
    Edge Detection on Satellite Images
    Terrain Slope Calculation
    Terrain Aspect Calculation
    LSTM Model for Time Series Prediction
    What You'll Learn:
    How to normalize and extract features from geospatial data
    Applying K-means clustering for spatial analysis
    Training and evaluating a Random Forest Classifier
    Building and training Convolutional Neural Networks (CNNs) using Keras
    Time series forecasting with ARIMA models
    Detecting anomalies with Isolation Forest
    Manipulating and visualizing geospatial data with GeoPandas and Folium
    Performing spatial joins and geospatial clustering
    Interpolating spatial data with Kriging
    Visualizing time-series geospatial data
    Edge detection on satellite images
    Calculating terrain slope and aspect from DEM data
    Predicting time series data using LSTM models
    Required Libraries:
    numpy
    pandas
    scikit-learn
    matplotlib
    keras
    statsmodels
    geopandas
    folium
    pykrige
    rasterio
    scipy
    We hope you find this tutorial helpful and informative. Don't forget to like, comment, and subscribe for more content like this!
    The code and data for this tutorial are available in my GitHub repository at: github.com/Aza....

КОМЕНТАРІ • 5

  • @AzadRasul1977
    @AzadRasul1977  Місяць тому +1

    The code and data for this tutorial are available in my GitHub repository at: github.com/Azad77/ML_Geospatial_Analysis.

  • @mediaasaad1271
    @mediaasaad1271 Місяць тому +1

    Dastt xosh dktor

  • @mustafayousifmohammed5393
    @mustafayousifmohammed5393 Місяць тому +1

    ❤دەستت خۆشبێت کاک دکتۆر❤❤❤