Questions tagged [lstm]

Question 1

Beginner ML practitioner here. I'm trying to do some time series forecasting on a fairly high resolution dataset that stretches over a long period of time. The values vary pretty widely over time: to ...

Question 2

I'm training an LSTM model to predict a stock price. This is what I do with my model training: ...

Question 3

I followed from this question. I have one folder path (C:\Users\alokj\OneDrive\Desktop\jupyter_proj\second_project_rotation_sun\Before_hour) which contains many ordered subfolders(time series data) ...

Question 4

I'm on working on classification problem My model architecture looks: ...

Question 5

I am from old school and I developed a machine learning solution that uses only sumation subtraction and comparisons, no multiplications, divisions or special functions as sigmoid or tangh. However, I ...

Question 6

I am unclear how an LSTM layer would interface with a fully connected layer and what this would look like visually as per the puthon code below. I am trying to understand and visualize this code. I'm ...

Question 7

I have collection of TEC data.My data sample for example the day1,day2,day3,day4. Case1: I have the following task to do: Training by the consecutive 3 days to predict the each 4th day. Each day data ...

Question 8

my goal is to create a LSTM that predicts one day in advance the price of a stock. My input data are XBTC prices along with technical indicators. These are the steps I follow: detrend the prices ...

Question 9

Friends here I want to ask about graph loss on my LSTM Pytorch modeling for stock price prediction, with like this is my modeling overfitting? for the results themselves are good, like this: MSE: ...

Question 10

Is it correct that there really is no difference between conducting a multi-step forecast with an LSTM and multiple 1-step forecasts where you update the data in between each 1 step forecast? The ...

Question 11

I am implementing in PyTorch an LSTM model to predict if the closing value of a stock will go up or down in the next 5 and 10 minutes. Specifically, I am using 24 years of 5 minute data with 19 ...

Question 12

I have a time series of values like below, where I'm looking at a history of sales: ...

Question 13

I'm trying to automate a process where someone has to tag when an animal jumps from one platform to another platform. Currently, a manual review of the video is done to note at which frame the animal ...

Question 14

I have been trying to understand the key differences between an LSTM layer with a timestep of 1 and a standard MLP (Dense) layer. Since LSTMs are often used for sequence data, I was wondering what ...

Question 15

I'm trying to implement RNN and LSTM , many-to-many architecture. I reasoned myself why BPTT is necessary in RNNs and it makes sense. But what doesn't make sense to me is, most of resources I went ...

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Questions tagged [lstm]

LSTM feature scaling with windowing?

What does it mean when validation loss increases over several epochs?

Training by 72 hours to predict next 24 hours by LSTM

statefull or stateless architecture?

Is possible to assess number of multiplication and sumation of a DL in a separete way?

How does an lstm layer interface with a dense layer?

Time series predictions with LSTM

Is Keras.utils.timeseries_dataset_from_array suitable for a LSTM for stock price prediction?

Is my Pytorch's LSTM underfiting

No difference between multiple 1 step forecasts and multistep forecast with LSTM

LSTM predicts the same value

Adding context specific information to RNN/LSTM at current time?

How do you create a model to track where a specific event starts and ends within a dataset?

What is the difference between an LSTM layer with a timestep of 1 and an MLP layer?

Why not back propagate through time in LSTM like RNN

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