How do create one model sequential with two models? I have two models, one a Keras application (vgg16 model) and a custom model and I would like to merge them i
Currently I'am training my Word2Vec + CNN for Twitter sentiment analysis about COVID-19 vaccine domain. I used the pre-trained GoogleNewsVectorNegative300 word
I'm trying to add utils from keras_unet in google colab, but I have a problem. import tensorflow as tfs from keras_unet import utils keras-unet init: TF versio
I would like to do a test about training a machine learning model on EC2 instance with only CPUs from jupyter notebook. The code is tensorflow 2.8. Based on the
i try to train a model that classified frames from my garden camera to detect different animals. My dataset has 8000 images, 2000 per class of squirrels, pigeon
I am trying to write a simple 1 dimensional convolution with a regression (1 dimensional float) output. model = Sequential() model.add(Conv1D(filters=1, kernel_
im trying to re train the mobilnet model with my own dataset and when I am trying to fit the model I get these error. mobile=tf.keras.applications.mobilenet.Mob
I am trying to use Tensorflow and Keras for a prediction model. I first read in my dataset that has shape (7709, 58), then normalize it: normalizer = tf.keras.l
currently I'am training my Word2Vec + LSTM for Twitter sentiment analysis. I use the pre-trained GoogleNewsVectorNegative300 word embedding. The reason I used t
I am working with TensorFlow Federated framework and designed a keras model for a binary classification problem. I defined the iterative process with tff.learni
I am a newbie in some sequential models in Tensorflow with Python. I have a transformation sequential model like the one below. It applies randomly to a given i
I have read in previous posts that using the TimeDistributed parameter in the LSTM model does not change the performance or how the layers work (It only gives a
I am trying to reproduce my code from online Jupyter Notebook (COURSERA) to my own local environment （Anaconda 3 Jupyter with CUDA installed) All Codes a
i am new to python and i am trying to create a model that can measure how similar movies are based on the movies description,the steps i followed so far are: 1.
I am trying to print all the 1290 parameters in dense_1 layer, but model.get_weights()[7] only show 10 parameters. How could I print all the 1290 parameters of
I'm trying to deploy my machine learning model to AWS Lambda function. I trained my model locally with Keras and got .h5 file. I zipped Tensorflow and Keras mod
How can I make this DNN model in tensorflow? 31 neurons in the first, 10 in the second, 5 in the third hidden layer, and 2 neurons in the output layer. The acti
I am getting the same prediction for different inputs. I am trying to use a regressional neural network. I want to predict values instead of class using neural
I'm working on a binary semantic segmentation problem. I built an UNet model with MobileNetV2 backbone. Here is my model code: def upsample(filters, size, apply
I want to convert this below RNN into bidirectional RNN, how can I do that? #Call the function and compile the model. model = RNN() model.summary() model.compil