Data_Assimilation
Data assimilation library
An implementation of an Autoencoder-based approach to data assimilation in physics and engineering applications
MSc Research project (6 months). Data Assimilation using Deep Learning (AEs). Imperial College Machine Learning MSc 2018-19
38 stars
2 watching
21 forks
Language: Python
last commit: over 5 years agoLinked from 1 awesome list
josephmisiti/awesome-machine-learningRelated projects:
| Repository | Description | Stars |
|---|---|---|
 code-kern-ai/refinery | A tool to help data scientists manage and annotate natural language data for training AI models | 1,405 |
 ujjwalkarn/datasciencepython | A curated list of tutorials and resources for learning Python for data science, machine learning, and other related topics. | 5,301 |
 sahith02/machine-learning-algorithms | A comprehensive resource for machine learning and deep learning algorithms | 295 |
 dustinstansbury/medal | A Matlab environment for training and using various deep learning architectures | 109 |
 aditya-grover/climate-learn | A library providing standardized access to climate data and machine learning models for statistical downscaling and temporal forecasting methods. | 314 |
 ecmwfcode4earth/deepr | Project aimed at downscaling global climate data to higher resolutions using deep learning techniques. | 24 |
 ayush1997/visualize_ml | A Python package for data analysis and visualization in machine learning | 198 |
 eurec4a/eurec4a-intake | Provides a standardized interface to various EUREC4A field campaign datasets | 17 |
 evetion/spacelidar.jl | A package for working with ICESat-2 & GEDI data in Julia | 24 |
 data-8/datascience | An introductory data science library for Python. | 635 |
 sergioburdisso/pyss3 | A Python package implementing an interpretable machine learning model for text classification with visualization tools | 336 |
 apmonitor/data_science | An online course using Python to analyze data and develop predictive models for heat transfer applications | 80 |
 juliaacademy/dataframes | An introduction to data wrangling with the DataFrames.jl package in Julia | 122 |
 datamllab/xdeep | Provides tools for interpreting deep neural networks | 42 |
 columbia-applied-data-science/rosetta | Tools and utilities for efficient data processing with a focus on text analysis. | 206 |