I am new to machine learning. I got the intermediate result of layer 31 of my CNN using the following code: conv2d = Model(inputs = self.model_ori.input, output
tf.keras.layers.TextVectorization layer maps text features to integer sequences, and since it can be added as a keras model layer it makes it easy to deploy the
I followed the tutorial here to try to train my model using CIFAR-100. But I'm getting this error. What do I do? ValueError: Data Params Error: The dataset labe
I'm currently implement the sequantial deep matching model (https://arxiv.org/abs/1909.00385) using tensorflow 2.3. And I included the preprocessing layer as pa
I want to distill knowledge from a teacher student to a student one, so I implemented a class named OCCSE that inherits from tf.keras.Model and accepts both tea
I'm trying to build a model which can be trained on both audio and video samples but I get this error ValueError: Please initialize `TimeDistributed` layer with
I am trying to make a toy example work; there is a simple submodel: Model: "sub_model" _________________________________________________________________ Layer
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 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
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
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
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'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
I have a LSTM model. which when I try to fit i get the error mentioned in the title. I have an array of timeseries data with multiple features I'm feeding as in