This question relates to the optimal setup for a multiple-input multiple-output Keras (Tensorflow) model given corresponding numpy arrays. For example, suppose
I'm using mnist dataset for my project on VsCode IDE. Following is the complete code. what is it that I'm doing wrong and how can I solve this error? # Import L
i'm pretty new to machine learning. I followed a tutorial to classify if the user is similing or not. I created this code: def get_model(input_size, classes=7):
I am using keras-tuner in order to obtain the best set of hyperparameters for my model. I can reproduce my problem for a random dataset: def generate_data(n_win
The HAR dataset should be analyzed using LSTM and 1D CNN. I need to check the graph of the change in loss and check the confusion matrix. I don't know how to ma
Could you help me with the code such that along with the dense layers also the last convolutional layer of Efficientnet is trained as well ? features_url ="http
I have a keras model trained for occupancy detection of parking spaces, which I load using keras.models.load_model(PATH_TO_MODEL). The input for the model is a
I've tried to run a code example (hosted on keras.io) regarding the handwriting recognition task. While playing with the code, I faced a TensorFlow-related issu
I'm implementing a UNet neural network but I'm having some issues while importing libraries. I found a solution for a couple of them, but I still have a problem
I have a very large file and I want to divide it into smaller ones for training. I've read about pickle files, so I split the large file into training-validatio
I want to train a model with self-generated matrices (word vectors). My data have the following datatypes: print(type(X)) print(type(X[0])) print(type(X[0][0]))
I am a beginner learning deep learning by Keras. The ImageDataGenerator class in Keras and the flow_from_directory function made it easy to label images. But al
I'm trying to improve my val accuracy as it is very low. I have tried changing the batch_size, the number of images being used for validation and training. Adde
I am getting the following error message when trying to run this AlexNET python code. Traceback (most recent call last): File "C:\Users\PycharmProjects\Local-
I trained my model with frozen backbone like: model.get_layer('efficientnet-b0').trainable = False Now, I unfreeze backbone, compile model, start training and
I am looking for a solution for a problem that has arisen when building a generic ANN for image classification in R. What I want to do is either: Design and com
I want to build an MLP classifier on iris dataset. Actually, I want to build a function that runs the model with N hidden units in the hidden layer and a loop t
Keras documentation about fine-tuning states that it is important to "keep the BatchNormalization layers in inference mode by passing training=False when callin
I am working on image classification using CNN. I am using below source code for that task. I am stuck with this error : AttributeError: 'NoneType' object has
from matplotlib import units import numpy as np from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense from tensorflow.keras