89 points by climate_tech 1 year ago flag hide 13 comments
climateml 1 year ago next
Excited to share our new case study on using machine learning to predict climate change patterns. We observed promising results and would love to hear your thoughts!
hackernoon 1 year ago next
@ClimateML Very interesting. Haven't seen an application of ML for climate change like this before. Thanks for sharing!
datahipster 1 year ago next
@hackernoon I'm curious if they leveraged any out-of-the-box ML libraries or built their own algorithms?
datahipster 1 year ago next
@hackernoon TensorFlow and Scikit-learn libraries typically provide the best balance of customizability and ease-of-use, I'd recommend taking a look at those first.
bigdataguru 1 year ago prev next
@ClimateML How did you handle collecting the necessary data for your ML model? What were some challenges and lessons learned?
climateml 1 year ago prev next
@BigDataGuru Collaborating with environmental agencies and using remote sensing tools helped us gather a good data set. Huge challenges included inconsistent data, limited historical records, and ensuring model generalization. Improving data quality and developing ensemble models helped overcome these obstacles.
climateml 1 year ago next
@BigDataGuru We used a mix of open-source libraries like TensorFlow, Scikit-learn, and XGBoost, and also built custom models using deep learning. Each had its merits for different types of analyses.
hackerlad 1 year ago prev next
Are there any good repos you suggest checking out for related work in this area? Would love to contribute!
climateml 1 year ago prev next
@hackerlad We've used the 'climate-ml' tag on GitHub to gather related work. Here's a curated list: https://github.com/ClimateML/awesome-climate-ml. Feel free to contribute!
bigdataguru 1 year ago prev next
This is an intriguing use case. Are there any policy or ethical implications that you've had to address during this project? @ClimateML
climateml 1 year ago next
@BigDataGuru Yes, ethical considerations include ensuring accuracy, non-maleficence, and fairness in predictions. For policy implications, considerations include impacts on current climate agreements, responsibility-sharing mechanisms, and informing regulations.
user12345 1 year ago prev next
Climate change is a significant problem. Using ML to predict the impacts helps create better strategies. Looking forward to seeing more studies in the future!
scientist543 1 year ago prev next
Awesome to see research progress on #climatechange! ML has the power to improve predictions. However, it's crucial to carefully consider its limitations and applications.