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Projects in Awesome Lists by geonextgis

A curated list of projects in awesome lists by geonextgis .

https://github.com/geonextgis/python-basics-learn-to-code-from-scratch

Welcome to "Python Basics: Learn to Code from Scratch"! This is a comprehensive course designed for beginners who want to learn Python from scratch. In this repository, you will find all the course materials, including notebooks, assignments, and solutions.

basic-programming course-materials fundamentals-of-programming jupyter-notebook object-oriented-programming python python3

Last synced: 24 Jan 2025

https://github.com/geonextgis/pyimgproc-image-processing-using-python

The "PyImgProc-Image-Processing-using-Python" GitHub repository is a comprehensive resource for image processing tasks implemented in Python.

Last synced: 24 Jan 2025

https://github.com/geonextgis/geomapper

A Python package demo for geospatial

geospatial jupyter mapping

Last synced: 24 Jan 2025

https://github.com/geonextgis/mastering-machine-learning-and-gee-for-earth-science

This repository is designed to empower individuals with advanced expertise in integrating Machine Learning techniques with Google Earth Engine (GEE).

Last synced: 24 Jan 2025

https://github.com/geonextgis/advancing-crop-yield-forecasting

This repository hosts the code and resources developed as part of my MSc Dissertation, focusing on advancing crop yield forecasting techniques.

crop-yield-prediction deep-learning google-earth-engine machine-learning python remote-sensing

Last synced: 24 Jan 2025

https://github.com/geonextgis/mathematics-for-data-science

This repository comprehensively guides the fundamental mathematical concepts crucial for mastering data science.

Last synced: 24 Jan 2025

https://github.com/geonextgis/data-wrangling-with-xarray

This comprehensive and practical course empowers learners to efficiently manipulate and analyze multidimensional data using the powerful Xarray library in Python.

Last synced: 24 Jan 2025

https://github.com/geonextgis/image-analysis-in-remote-sensing-with-python

This GitHub repository provides a comprehensive collection of Python scripts, tools, and examples for image analysis in remote sensing applications. It aims to assist researchers, scientists, and developers in processing and extracting valuable information from remote sensing imagery.

Last synced: 24 Jan 2025

https://github.com/geonextgis/geonextdemo

A Python package demo for geospatial

geospatial jupyter mapping

Last synced: 25 Dec 2024

https://github.com/geonextgis/geolens

A python package demo.

Last synced: 24 Jan 2025

https://github.com/geonextgis/geenext

A python package to extend the capabilities of Google Earth Engine in the field of Al and ML.

Last synced: 24 Nov 2024

https://github.com/geonextgis/latex-full-tutorial-for-beginners

Welcome to the LaTeX Full Tutorial for Beginners repository! 📄✨ This comprehensive guide is designed for newcomers to LaTeX, a powerful typesetting system commonly used for creating documents, articles, and academic papers. Whether you're a student, researcher, or enthusiast, this tutorial covers everything from the basics to advanced topics.

Last synced: 24 Jan 2025

https://github.com/geonextgis/end-to-end-machine-learning

Welcome to the "End-to-End Machine Learning" repository, your comprehensive guide to mastering the entire lifecycle of machine learning projects.

Last synced: 24 Jan 2025

https://github.com/geonextgis/predictive-modeling-of-groundwater-potential-zones-in-bankura-district

The primary goal of this research is to develop an accurate and reliable predictive model, using advanced machine learning techniques, to delineate Groundwater Potential Zones (GPZs) in the Bankura District of West Bengal, India, by utilizing the Central Ground Water Board (CGWB) Ground Water Level Depth data.

Last synced: 24 Jan 2025

https://github.com/geonextgis/geonextgis.github.io

My personal website

Last synced: 24 Jan 2025

https://github.com/geonextgis/data-science-bootcamp-with-python

This comprehensive course is designed to take you from a beginner level to a proficient level in data science with Python. The course covers the essentials of data science, including data exploration and visualization, data cleaning and wrangling, statistical analysis, and machine learning.

Last synced: 24 Jan 2025