I have a large list of numpy arrays that I want to feed into a TensorFlow model. I can not concatenate the lists into one due to RAM memory issues. Below, I hav
I am working on an image classification task to classify among cars and buses. The problem is that in most car images, there is buses in the background and vice
I am trying to install and use a package called FinRL. This package has a dependency, StableBaselines which uses tensorflow. It says in FinRL documentation that
I used a convolutional neural network (CNN) for training a dataset and I want to plotting accuracy for this. Before, I tried to use matplotlib but I couldn't su
I've problems integrating Bert Embedding Layer in a BiLSTM model for text classification task. My dataset is in the form where each row has 2 columns: text and
The result is below，I run the project stylegan2, but it fails. So I need help. The link is https://github.com/NVlabs/stylegan2 File "/home/ubuntu/worksp
I trained my network several times and I already got some results. Then I found out about the Keras tuner and wanted to find the best hyperparameters with it. b
This question is a follow-up of tensorflow 2 TextVectorization process tensor and dataset error I would like to make do a word embedding for the processed text
let say I got two tensor where tensor A has shape (100,7), tensor B has shape (100,7,64). I want to pick the first item from A and B and multiply them by tf.mat
Using tensorflow, I'm trying to reimplement the following architecture (for now I'm focusing on the Generator part): What I've done for now has been defining t
I am trying to use Tensorflow to create a recommendation system. What I want to do is to read data from two csv files, one containing 'item_id' and the other co
So I have a problem when train deep learning with BERT with tensorflow which contain text dataset. So i want to fit() the model but got an error when training.
let say I got two tensor where tensor A has shape (100,7), tensor B has shape (100,7,64). I want to pick the first item from A and B and multiply them by tf.mat
when running the following code from a jupyter notebook in the ec2 instance: from keras.datasets import imdb the following error message pops out: ModuleNotFoun
I would like to process text with tensorflow 2.8 on Jupyter notebook. my code: import re import string import tensorflow as tf from tensorflow import keras from
I've loaded in my train and validation sets from CIFAR10 like so: train = tfds.load('cifar10', split='train[:90%]', shuffle_files=True) validation = tfds.load('
I have list of labels corresponding numbers of files in directory example: [1,2,3] train_ds = tf.keras.utils.image_dataset_from_directory( train_path, label
import pandas as pd import numpy as np from sklearn.preprocessing import StandardScaler from keras import Sequential from tensorflow.keras.layers import Dense f
I want to checkpoint model whenever validation precision and recall improves - this is on top of validation accuracy and validation loss. So I have added follow
I'm trying to call a TensorFlow model on a linspace but I can't seem to get even a very simple example (based on https://www.tensorflow.org/api_docs/python/tf/k