On the other hand, causality would enable generalization (i.e. ability for a model to adapt to new data) and explainability. Causal inference has great synergies with certain areas of ML such as Reinforcement Learning.
And this can have devastating consequences when systems make recommendations or decisions that have major impacts on our lives (e.g. self-driving cars, medical diagnostics and recommendations, drug development).
@Gleensite and its Team have been awarded and named as the โInternational Property Technology Innovation Leadersโ by @AcademyProptech Academy ๐ฅ๐
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โThey are pioneers of the property technology worldwide!โ
What an honour, thank! ๐
#proptech#innovation#Analytics#technology
โEverything is connected, and we want to make those causal threads more visible so that people around the world can make better decisions.โ
We spoke to @AGarciaManic, co-founder of predictive analytics software start-up, @Gleensite, in our latest meet the members blog.
Do you need help digitalising your real estate data?
Check out our latest coverage in @placetech to find out how we are helping @AlliedLondon.
Read here ๐
https://t.co/b0WSKVnpbn