santonugoswami Goto Github PK

geospatial-machine-learning

A curated list of resources focused on Machine Learning in Geospatial Data Science.

geostatspy

Reimplementation of GSLIB, Spatial Data Analytics and Geostatistics in a Python package.

gis-tools-for-hadoop

The GIS Tools for Hadoop are a collection of GIS tools for spatial analysis of big data.

gmm_based_change_detection_framework_using_very_high_resolution_satellite_imagery

google_earth_engine_notebook

A walkthrough of some Google Earth Engine Features, as well as using the data in TensorFlow

gramex

A visual analytics platform to build data-based web apps with less code.

hands-on-machine-learning

Contains Jupyter Notebooks/Resources provided by the author and my work on problem sets.

handson-ml

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

healthycountryai

An adaptable framework using AI to monitor ecosystem health

hyftech-hyperspectral-shallow-deep-feature-extraction-toolbox

This Toolbox includes Hyperspectral Feature Extraction Techniques including Unsupervised, Supervised, and Deep Feature Extraction

hyperparameter-optimization

Implementation of Bayesian Hyperparameter Optimization of Machine Learning Algorithms

hyperspectral

Deep Learning for Land-cover Classification in Hyperspectral Images.

imd

interpretable-ml-book

Book about interpretable machine learning

intoli-article-materials

All of the supporting materials for articles from Intoli's blog.

it-cfp-list

List of Call For Papers for IT conferences

lcd

The Normalized Difference Vegetation Index (NDVI) for the study time period is calculated and then compared to the maximum and minimum NDVI from a baseline range of years in order to calculate Relative Greenness (RG). The change in RG from the previous year is found, and this allows the user to identify abrupt change in vegetation. Normalized Burn Ratio (NBR) and USDA Croplands Dataset have been added as additional datasets that can help establish if the change was caused by a fire or by a change in crop type. Recent available NAIP imagery for the study area is also included, as an example of what is available for high resolution imagery within GEE. Based on a date input by the user, the map viewer displays the RG, the change in RG, the percent change in RG, and the NBR, along with the Cropland layer from that year and NAIP imagery taken closest in time to the requested display date.

machine-learning

Notes for machine learning

machine-learning-1

In this repository, I will upload some projects I have been working on. These include building algorithms from scratch, as well as some applications of these.

machine-learning-project-walkthrough

An implementation of a complete machine learning solution in Python on a real-world dataset. This project is meant to demonstrate how all the steps of a machine learning pipeline come together to solve a problem!

machine-learning-projects

Machine Learning Experiments and Work

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

machinelearning

Machine Learning & Data Science Notebooks

matplotlib-gallery

Examples of matplotlib codes and plots

matplotlib_tutorial

Source code to go along with my tutorial to learn data visualization with the matplotlib library of Python

ml-articles

Articles on machine learning

ml-youtube-courses

📺 Discover the latest machine learning / AI courses on YouTube.

mml-book.github.io

Companion webpage to the book "Mathematics For Machine Learning"

models

Models and examples built with TensorFlow