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### Deep Learning Simplified Repository (Proposing new issue)
:red_circle: **Project Title** : NYC Agency Social Media Engagement using DL
:red_circle: **Aim** : The aim of this project is to analyz…
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Looking at custom networks and LSTMs and RNNs in particulat. It isn't very clear how these might be added to an agent.
It may just be a case of additions being made to the docs.
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In financial derivatives hedging, feature extraction is locating and extracting useful data or features from raw data that may be utilized to make forecasts or choices. These characteristics may inclu…
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# 호다닥 공부해보는 RNN 친구들(1) - RNN(Recurrent Neural Networks) - 호롤리한 하루
Overview 호다닥 공부해보는 시리즈가 2편째가 되었습니다. 이번에는 머신러닝의 꽃이라고도 불리는 RNN을 들고 왔습니다. 다음 포스팅에서는 RNN친구들인 LSTM과 GRU도 소개하도록 하겠습니다.
[https://gruuuuu.gi…
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We now have the reasonable capacity to perform time series forecasting via reduction to regression. Some bespoke forecasting architectures would also be good to implement too, though.
@mloning thi…
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Hello, first of all, I want to thank you for your great work. Is there any possibility that you make some documentation about the library on how to use to build lstm networks?
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we know if we have more data ,time and power we can do more accuracy predictions, we can do pre-computations and creating one powerful model, but the behavior of each sensor is different
we think how…
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Given that we are working with time series data, we can use LSTM neural networks.
See this group that did weather forecasting with time series data for inspiration:
https://kendrik-wah.github.io/c…
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### Description
Hi creators of Stellargraph. First of all, great work on this package!
I have one question, I would like to also work with time-series on graphs with graph convolutional networks…
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Hi!
Axon beginner here.
I struggle to figure out how to write a very simple RNN network. Basically I want to rewrite this pytorch example from [a tutorial](https://pytorch.org/tutorials/intermedia…