Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

💿 Free software that works great, and also happens to be open-source Python.

The "Python Machine Learning (2nd edition)" book code repository and info resource

Code for Tensorflow Machine Learning Cookbook

Dask tutorial

use numpy, scipy, and tensorflow to implement these basic ML model and learning algorithm

Guide explaining and implementing fundamental machine learning algorithms in Python

Code for the paper "Spatio-Temporal Neural Networks for Space-Time Series Modeling and Relations Discovery"

Pythonic multiple doppler code based off the 3D variational technique

Collection of examples for pytroll satellite data processing

Code for neural network parameterization project

Predicting Air Pollution in Beijing, China using Deep Neural Nets

InMAP reduced-form air quality model for fine particulate matter (PM2.5)

This project has applied some Machine Learning techniques to analyse and predict the Air Quality in Beijing.

A platform for impacted communities to understand their local air quality and advocate for environmental justice.

¡AnDA! is a Python library for the Analog Data Assimilation.

Jupyter notebooks for the Python session of the 2018 Earth Engine User Summit.

Python implementation of the Kolmogorov Zurbenko filter

Plotting data on the interactive maps, IPython Notebook friendly.

Sparse Matrix Multiplication Experiments

Modelling dynamic behavior of time series using LSTM

Talk on Understanding and Implementing Recurrent Neural Networks using Python - By: Anmol Krishan Sachdeva at GeoPython, Switzerland, 2018