Climate Analytics: Difference between revisions
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Climate analytics aims to quantify the expected financial impacts of climate change, thereby incentivizing investors and companies to act. Machine Learning can contribute to this by helping forecast prices in carbon markets, identifying climate risks and investment opportunities, and quantifying the monetary impact of climate change on supply and demand by using data-based approaches. |
Climate analytics aims to quantify the expected financial impacts of climate change, thereby incentivizing investors and companies to act. Machine Learning can contribute to this by helping forecast prices in carbon markets, identifying climate risks and investment opportunities, and quantifying the monetary impact of climate change on supply and demand by using data-based approaches. |
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Latest revision as of 14:39, 14 January 2021
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Climate analytics aims to quantify the expected financial impacts of climate change, thereby incentivizing investors and companies to act. Machine Learning can contribute to this by helping forecast prices in carbon markets, identifying climate risks and investment opportunities, and quantifying the monetary impact of climate change on supply and demand by using data-based approaches.