Running Anaconda and installed: Keras = 2.4.3 TensorFlow = 2.4.0 However, when importing Keras - I get "Keras requires TensorFlow 2.2 or higher". Tried uninstal
hello everyone i am trying to train a model using cnn and keras but the training don't finish and i got this warning and it stops training , i don't know why an
Beginner here. I recently converted my images to grayscale using opencv. Then I used those images for training. When I was training, there was an error. "Invali
Hi everyone I am using pip as package manager, and I receive the following DeprecationWarning when running my tests. I know that sometimes Warnings can be the B
fellow coders. I am trying to figure out ways to add a confusion matrix to the output of my Mobilenet-based multiclass classifier. Being a biologist with limite
I want to get KerasRegressor history but all the time I get (...) object has no attribute 'History' ''' # Regression Example With Boston Dataset: Standardized a
My notebook was working up till today. At the beginning of my colab notebook I install tf-nightly, but now it is giving me this error: -------------------------
I have trained a model and now my task was to test it on unseen images from the internet. Originally the model was trained on CIFAR-10 so for the model I chose
I have been working on a tensorflow model that predicts short term positive and negative trends in the stock market using momentum indicators. I have the model
I'm learning ObjectDetection from this website I have installed ImageAI,Tensorflow and Keras. Then when I run this in python from imageai.Detection import O
I am trying to fine tune a Huggingface Bert model using Tensorflow (on ColabPro GPU enabled) for tweets sentiment analysis. I followed step by step the guide on
screenshot showing the model training stuck at epoch 1 without throwing error I am using google colab pro and here is my code snippet batch_size = 32 img_heigh
I got this error message when declaring the input layer in Keras. ValueError: Negative dimension size caused by subtracting 3 from 1 for 'conv2d_2/convolu
Here is my classification problem : Classify pathological images between 2 classes : "Cancer" and "Normal" Data sets contain respectively 150 000 and 300 000 im
I have a subclassed model with some custom attributes like this: class MyModel(tf.keras.Model): def __init__(self, *args, my_var, **kwargs): super()
I have a subclassed model with some custom attributes like this: class MyModel(tf.keras.Model): def __init__(self, *args, my_var, **kwargs): super()
I would like to get to know the real sequence_length in Keras for a LSTM/RNN. Unfortunately, when I print the model I only get None all the time as a value. Her
I am trying to make a custom loss function where I perform an inverse fast Fourier transform to a set of data and then do the following calculations. When I run
I'm running a toy model for learning, on Ubuntu 21.10, in a conda environment that comprises python 3.74, keras 2.4.3 and talos 1.0, among many other packages.
so I have 2 images, img1 and img2 both with shape=(20,20), to which I expand_dims to (1,20,20) 1 being batch size and feed them to the network