Made-With-ML VS ETCI-2021-Competition-on-Flood-Detection

Compare Made-With-ML vs ETCI-2021-Competition-on-Flood-Detection and see what are their differences.

ETCI-2021-Competition-on-Flood-Detection

Experiments on Flood Segmentation on Sentinel-1 SAR Imagery with Cyclical Pseudo Labeling and Noisy Student Training (by sidgan)
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Made-With-ML ETCI-2021-Competition-on-Flood-Detection
51 1
35,328 150
- -
6.8 1.8
4 months ago almost 2 years ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
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Made-With-ML

Posts with mentions or reviews of Made-With-ML. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-06-25.

ETCI-2021-Competition-on-Flood-Detection

Posts with mentions or reviews of ETCI-2021-Competition-on-Flood-Detection. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning ETCI-2021-Competition-on-Flood-Detection yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing Made-With-ML and ETCI-2021-Competition-on-Flood-Detection you can also consider the following projects:

zero-to-mastery-ml - All course materials for the Zero to Mastery Machine Learning and Data Science course.

FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

practical-mlops-book - [Book-2021] Practical MLOps O'Reilly Book

mlops-zoomcamp - Free MLOps course from DataTalks.Club

mlops-course - Learn how to design, develop, deploy and iterate on production-grade ML applications.

Copulas - A library to model multivariate data using copulas.

awesome-mlops - A curated list of references for MLOps

mlattacks - Machine Learning Attack Series

SBERT-for-Question-Answering-on-COVID-19-Dataset - Sentence Bert for Question-Answering on COVID-19 Open Research Dataset (CORD-19)

fake-s3 - A lightweight server clone of Amazon S3 that simulates most of the commands supported by S3 with minimal dependencies

stanford-cs229 - πŸ€– Exercise answers to the problem sets from the 2017 machine learning course cs229 by Andrew Ng at Stanford

unet - unet for image segmentation