Land Cover Classification Random Forest

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.
Dr. Sander Ali Khowaja
Gaussian Process Optimization using GPy

End of maintenance for GPyOpt Dear GPyOpt community! We would like to acknowledge the obvious. The core team of GPyOpt has moved on, and over the past

Sheffield Machine Learning Software 847 Dec 19, 2022
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification

Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth

5 Dec 06, 2022
onelearn: Online learning in Python

onelearn: Online learning in Python Documentation | Reproduce experiments | onelearn stands for ONE-shot LEARNning. It is a small python package for o

15 Nov 06, 2022
Neural Machine Translation (NMT) tutorial with OpenNMT-py

Neural Machine Translation (NMT) tutorial with OpenNMT-py. Data preprocessing, model training, evaluation, and deployment.

Yasmin Moslem 29 Jan 09, 2023
Uses WiFi signals :signal_strength: and machine learning to predict where you are

Uses WiFi signals and machine learning (sklearn's RandomForest) to predict where you are. Even works for small distances like 2-10 meters.

Pascal van Kooten 5k Jan 09, 2023
A collection of Machine Learning Models To Web Api which are built on open source technologies/frameworks like Django, Flask.

Author Ibrahim Koné From-Machine-Learning-Models-To-WebAPI A collection of Machine Learning Models To Web Api which are built on open source technolog

Ibrahim Koné 2 May 24, 2022
YouTube Spam Detection with python

YouTube Spam Detection This code deletes spam comment on youtube videos based on two characteristics (currently) If the author of the comment has a se

MohamadReza Taalebi 5 Sep 27, 2022
Datetimes for Humans™

Maya: Datetimes for Humans™ Datetimes are very frustrating to work with in Python, especially when dealing with different locales on different systems

Timo Furrer 3.4k Dec 28, 2022
A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and A* Search (Manhattan Distance Heuristic)

A Python-based application demonstrating various search algorithms, namely Depth-First Search (DFS), Breadth-First Search (BFS), and the A* Search (using the Manhattan Distance Heuristic)

17 Aug 14, 2022
Made in collaboration with Chris George for Art + ML Spring 2019.

Deepdream Eyes Made in collaboration with Chris George for Art + ML Spring 2019.

Francisco Cabrera 1 Jan 12, 2022
Mesh TensorFlow: Model Parallelism Made Easier

Mesh TensorFlow - Model Parallelism Made Easier Introduction Mesh TensorFlow (mtf) is a language for distributed deep learning, capable of specifying

1.3k Dec 26, 2022
A python library for Bayesian time series modeling

PyDLM Welcome to pydlm, a flexible time series modeling library for python. This library is based on the Bayesian dynamic linear model (Harrison and W

Sam 438 Dec 17, 2022
InfiniteBoost: building infinite ensembles with gradient descent

InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De

Alex Rogozhnikov 183 Jan 03, 2023
This is my implementation on the K-nearest neighbors algorithm from scratch using Python

K Nearest Neighbors (KNN) algorithm In this Machine Learning world, there are various algorithms designed for classification problems such as Logistic

sonny1902 1 Jan 08, 2022
A game theoretic approach to explain the output of any machine learning model.

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

Scott Lundberg 18.2k Jan 02, 2023
Model factory is a ML training platform to help engineers to build ML models at scale

Model Factory Machine learning today is powering many businesses today, e.g., search engine, e-commerce, news or feed recommendation. Training high qu

16 Sep 23, 2022
Python Automated Machine Learning library for tabular data.

Simple but powerful Automated Machine Learning library for tabular data. It uses efficient in-memory SAP HANA algorithms to automate routine Data Scie

Daniel Khromov 47 Dec 17, 2022
LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms

LILLIE: Information Extraction and Database Integration Using Linguistics and Learning-Based Algorithms Based on the work by Smith et al. (2021) Query

5 Aug 06, 2022
PennyLane is a cross-platform Python library for differentiable programming of quantum computers

PennyLane is a cross-platform Python library for differentiable programming of quantum computers. Train a quantum computer the same way as a neural ne

PennyLaneAI 1.6k Jan 01, 2023
Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along with material in the form of Jupyter Notebooks.

Databricks Certification Spark Databricks Certified Associate Spark Developer preparation toolkit to setup single node Standalone Spark Cluster along

19 Dec 13, 2022