Land Cover Classification Random Forest

Last update: Jan 21, 2022

Overview

Land_Cover_Classification_Random_Forest

You can perform Land Cover Classification on Satellite Images using Random Forest and visualize the result using Earthpy package. Make sure to install the required packages and such as

pip install gdal pip install earthpy

These packages require C++ build dependencies so be sure to install Visual C++ 14.0 or higher. If you want to avoid all hussle of installing packages then just opt for Google Colab. Be sure to upload images and ground truth file from The Sundarbans Dataset (https://earthdata.nasa.gov/worldview/worldview-image-archive/the-sundarbans). For ease I am also uploading the data with this repository

Owner

Dr. Sander Ali Khowaja

Assistant Professor, Department of Telecommunication, Faculty of Engineering and Technology.

GitHub Repository

A Streamlit demo to interactively visualize Uber pickups in New York City

Streamlit Demo: Uber Pickups in New York City A Streamlit demo written in pure Python to interactively visualize Uber pickups in New York City. View t

230 Dec 28, 2022

The code from the Machine Learning Bookcamp book and a free course based on the book

5.5k Jan 09, 2023

A high-performance topological machine learning toolbox in Python

giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G

632 Dec 29, 2022

Massively parallel self-organizing maps: accelerate training on multicore CPUs, GPUs, and clusters

Somoclu Somoclu is a massively parallel implementation of self-organizing maps. It exploits multicore CPUs, it is able to rely on MPI for distributing

239 Nov 10, 2022

A demo project to elaborate how Machine Learn Models are deployed on production using Flask API

This is a salary prediction website developed with the help of machine learning, this makes prediction of salary on basis of few parameters like interview score, experience test score.

1 Feb 10, 2022

Binary Classification Problem with Machine Learning

Binary Classification Problem with Machine Learning Solving Approach: 1) Ultimate Goal of the Assignment: This assignment is about solving a binary cl

0 Jan 20, 2022

Project to deploy a machine learning model based on Titanic dataset from Kaggle

kaggle_titanic_deploy Project to deploy a machine learning model based on Titanic dataset from Kaggle In this project we used the Titanic dataset from

8 May 23, 2022

Banpei is a Python package of the anomaly detection.

Banpei Banpei is a Python package of the anomaly detection. Anomaly detection is a technique used to identify unusual patterns that do not conform to

282 Jan 03, 2023

MLR - Machine Learning Research

Machine Learning Research 1. Project Topic 1.1. Exsiting research Benmark: https://paperswithcode.com/sota ACL anthology for NLP papers: http://www.ac

69 Oct 20, 2022

Interactive Parallel Computing in Python

Interactive Parallel Computing with IPython ipyparallel is the new home of IPython.parallel. ipyparallel is a Python package and collection of CLI scr

2.3k Dec 30, 2022

Machine-care - A simple python script to take care of simple maintenance tasks

Machine care An simple python script to take care of simple maintenance tasks fo

2 Jul 10, 2022

机器学习检测webshell

ai-webshell-detect 机器学习检测webshell,利用textcnn+简单二分类网络,基于keras,花了七天检测原理: 从文件熵文件长度文件语句提取出特征,然后文件熵与长度送入二分类网络,文件语句送入textcnn 项目原理,介绍,怎么做出来的

56 Dec 14, 2022

The Emergence of Individuality

16 Jul 20, 2022

Scikit learn library models to account for data and concept drift.

liquid_scikit_learn Scikit learn library models to account for data and concept drift. This python library focuses on solving data drift and concept d

7 Nov 18, 2021

Model Agnostic Confidence Estimator (MACEST) - A Python library for calibrating Machine Learning models' confidence scores

95 Dec 28, 2022