] You can check the Network Model and Result from the Photos. Result datas are stuck in the "average band" and can't forecasting the exact value. I used a 3ye
Currently I'm working on an image classification issue and created the following code based on a tutorial online - Image Classification using Keras. The code w
I have time series training data of about 5000 numbers. For each 100 numbers, I am trying to predict the 101st. At the end of the series, I would put in the pre
From the Keras documentation: dropout: Float between 0 and 1. Fraction of the units to drop for the linear transformation of the inputs. recurrent_dropout: F
After training a PyTorch model on a GPU for several hours, the program fails with the error RuntimeError: cuDNN error: CUDNN_STATUS_INTERNAL_ERROR Trainin
I am applying LSTM on a dataset that has 53699 entries for the training set and 23014 entries for the test set. The shape of the input training set is (53699,4)
I'm trying to copy a LSTM model that I found from here: Stock Market-Predict volume with LSTM model I'm getting stuck on the last line of code. Specifically, th
I train the following model based on GRU, note that I am passing the argument stateful=True to the GRU builder. class LearningToSurpriseModel(tf.keras.Model):
I wish to experiement with noisy GRU states instead of resetting them to zero for each batch. I try below an implementation. My initial code was resetting initi
Continuation from previous question: Tensorflow - TypeError: 'int' object is not iterable My training data is a list of lists each comprised of 1000 floats. For
I implement a model including a LSTM layer by subclassing the keras.Model. The following is the code I used. import tensorflow as tf from tensorflow import ker