My input is a array of 64 integers. model = Sequential() model.add( Input(shape=(68,), name="input")) model.add(Conv1D(64, 2, activation="relu", padding="same",
I'm Trying to making DNN using Wide Deep Nural Network using keras the following code produces the following after trying to implement it, I also making my cust
I am working on a project on Reinforcement Learning - and completely new at this. I installed keras-rl as pip install keras-rl, however it caused an error as ma
I am trying to predict the of number peaks in time series data by using a CNN and keep on getting a data shape error. My data looks as follows: X = list of 520
Hello I have being using tensorflow and keras for a while. I use this packages to build neural networks. As I work on CPU I was used to recive a message like th
My data contains 520 time series, each of length 2297: X_train = numpy.ndarray of shape (338, 2297, 1) X_val = numpy.ndarray of shape (85, 2297, 1) X_test = num
I have been trying to revisit my python code for prediction on neural network and i realized after running the code that model.predict_classes is deprecated sin
When I try to fit my model i get an error. Here is the code: model = Sequential() model.add(LSTM(128, activation='relu', input_shape=(trainX.shape[1], trainX.sh
I have a list of images each with shape=(20, 20, 1), there are 10 images so len(list)=10. How can I convert this into tensor/array with shape=(10,20,20,1)? Than
import keras print(keras.__version__) #2.3.0 from keras.models import Sequential from keras.layers import Input, Dense,TimeDistributed from keras.models import
i am new in using pyspark with elephas and tensorflow i am trying to train a deep learning model inside pyspark using elephas module my code : https://www.kaggl
I am new to TensorFlow's tf.data.Dataset and I am trying to use it on my data that I loaded with pandas dataframe as follows: Load the input date (df_input):
I have the following Keras DNN model and have imported necessary Keras & Yellowbrick libraries: optimizer = RMSprop(0.001) finalDNNModel_wrap = KerasClassif
I am working on an image recognition project using TensorFlow and Keras, that I would like to implement to my Android project. And I am new to Tensorflow... I w
I am fairly new to tensorflow and dont have any idea what is going wrong. It keeps me showing this "bad marshall error" which i cant seem to understand is cause
I have a task to load and extract feature embeddings from images. I've working solutions that utilize two different ways of loading the image: tensorflow.keras.
my code: from keras.preprocessing.image import load_img, img_to_array from keras.preprocessing.image import smart_resize import numpy as np #load pretrained mo
I'm trying to make an AI attempting to predict numbers from prime number sequence, but my model outputs "[[nan]]". My csv file is formatted like this: number of
Background My sentiment analysis research comes across a variety of datasets. Recently I've encountered one dataset that somehow I just cannot train successfull
I have a keras model, which takes a 10x10x1 array as input. For example: array = np.array([ [[0],[0],[0],[0],[0],[0],[0],[0],[0],[0]], [[0],[0],[0],[0],[0],[0],