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Feature to automate a variety of tasks associated with training a predictive machine learning model to generate market forecasts given a set of input signals. In general, this aims would be a sandbox …
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## Start with the `why`:
The `why` of this effort (and initial research) is that any many applications depth cameras (and even sometimes LIDAR) are not sufficient to successfully detect objects in …
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@mooskagh
I tried to compile your lc0 version with:
tensorflow_cc,
CUDA,
cuDNN.
I fixed some compile errors below.But still not able to compile on linux.I wonder that anybody compiled that…
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I wonder, is there any chances the existing data could be used to maybe _predict_ future values?
We could either show a notification or a hint based on some predicted future state.
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[Streaming weak submodularity: Interpreting neural networks on the fly](https://papers.nips.cc/paper/6993-streaming-weak-submodularity-interpreting-neural-networks-on-the-fly)
In many machine learnin…
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Hi
I am trying to implement your MNIST TR classifier:
```
# Import Necessary Pytorch Modules
import torch
import torch.nn as nn
from torch import Tensor
from tednet.tnn import tensor_ring a…
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Windows folder structure (\) does not work on linux (/). I had to replace all asset value strings with / for them to load. Should be an easy thing to fix.
If there is any documentation on what the di…
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We have seven jobs to do, please choose one of them. For visualisation, there are two candidate algorithms, and we need one person to do the visualisation. Please reply below for your decision.
1.…
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Looking at the tutorials, the ordering looks a bit random. Perhaps we should reorder the tutorials, roughly in order from least to most advanced, to make it easier to understand them? I'd suggest some…
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https://arxiv.org/pdf/1706.02515.pdf
Deep Learning has revolutionized vision via convolutional neural networks (CNNs) and natural language processing via recurrent neural networks (RNNs). However, …
leo-p updated
7 years ago