Reddit - Neural Networks
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Reddit - Neural Networks
1d ago
I'm training a simple neutral network with 2 linear and a relu (experimented with dropout layers in the beginning later) but the model is unable to learn or converge. My dataset has a lot of zeros(~97%) and then some values between 0-40(3%). How made make my model learn. Are there any tricks to this? Let me know if there's a better subreddit to post this question as well. Thanks!
submitted by /u/investmentwholesome
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Reddit - Neural Networks
4d ago
I am trying to implement this paper https://arxiv.org/pdf/1706.01151, which is basically trying a Neural Network to predict bpsk transmission.
I have 30 transmitters each sending bpsk signal, so a total of 230 possible signals. On top of which noise will be added. I need a good way to train my model as I obviously can train only on a small subset of all possible data.
This is how paper mentions the training: We train the network using a variant of the stochastic gradient descent method [20],[21] for optimizing deep networks, named Adam Optimizer [22]. We used batch training with 5000 random d ..read more
Reddit - Neural Networks
6d ago
Hi there,
I've created a video here where I explain how cross-validation works and why it is useful.
I hope it may be of use to some of you out there. Feedback is more than welcomed! :)
submitted by /u/Personal-Trainer-541
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Reddit - Neural Networks
1w ago
I have been looking for any starting point prepare multivariate spatio-temporal forecasting data, but all the examples I found so far have been using univariate models that only use the adjacency matrix.
Are there any good explanations or code implementations that I could start exploring?
submitted by /u/dyenamitewlaserbeam
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Reddit - Neural Networks
1w ago
submitted by /u/Difficult_Current_57
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Reddit - Neural Networks
1w ago
What do you think about this statement? The reason neural network could produce human-like AI such as chat GPT, Alphago is because it utilizes nonlinearity in each layer of the nodes. Neurons are nonlinear too. Nonelinearity is strongly related to the emergence of consciousness. Utilizing more dimension can unlock higher (ie vector with infinite dimension) consciousness.
ChatGPT response:
The statement you've presented reflects an intriguing perspective, but it's crucial to approach it with a critical eye. Let's break down the various components of the statement:
Neural Networks and Nonlinea ..read more