I am trying to make an image classifier. When running this it does okay on the first epoch, but at the beginning of the second epoch it runs out of training data, gives me a warning, then just starts the third epoch, and when thats done, it gives me another error on epoch 4, and so on.

These are the packages I am trying to work with Python 3.10 and Keras Version 3.3.2 and Tensorflow version 2.16.1. I am getting errors naming that some of the modules are not present. How do I make the modules work without upgrading or degrading the versions?

I am working on an AI NLP model that classifies text in 6 categories. I can’t disclose the specific purpose of the model, sorry. Here it is: –

I have every package installed (tensorflow, keras, sci-kit, etc.).

I tried to install the tensorflow and keras with anaconda, but I did not succeed. The advice given at this link text did not help. Could you describe in detail how to install the library for Python 3.10.2. Additional info: Windows 10, x64, Intel(R) Pentium(R) Gold G6400 CPU.
Thank you!

I am generating a model to read QR codes. I figured that I kept receiving a test accuracy of 0 and a training accuracy of 1.0 due to overfitting. Once I reduced the layers in my CNN, I got a training accuracy of 98% and training loss of 3, while a testing accuracy of 0% and a testing loss of 6.

I’m using Tensorflow 2.16.1. Ultimately, for each training sample, I need to create hidden and cell tensors for use with LSTM. Different training samples require different sized hidden/cell tensors.

Note: It’s crucial to use export TF_USE_LEGACY_KERAS=1 to ensure that TensorFlow utilizes Keras version 2.* for compatibility reasons.

I’m trying to load a Keras LTC model that has the following layers:

I am using the following code to define and compile a Keras model. Then when I print the model.summary() I am still getting unbuilt and erroneous summary. I am using Python3.10.12 and tensorflow 2.16.1. Please do not hesitate to reach out for any additional information you need.