I am following the mathswork tutorial for transfer learning on the GoogLenet, and when it comes to the freezeWeights function, it just doesn't work for me, and
I want to perform hyperparameter optimization on my transfer learning model using Keras Tuner. I am not sure how to do this since I have two stages of training,
I was watching https://developer.apple.com/videos/play/wwdc2019/428/, where Transfer Learning is used for text classification in Create ML. I wanted to do the s
I want to retrieve the hyperparameters after training a time-series model using Facebook Prophet, so that I can use the learned values in a second model. Here's
If I freeze my base_model with trainable=false, I get strange numbers with trainable_weights. Before freezing my model has 162 trainable_weights. After freezin
If I freeze my base_model with trainable=false, I get strange numbers with trainable_weights. Before freezing my model has 162 trainable_weights. After freezin
I'm a beginner in object detection field. First, I followed YOLOv4 custom-train from here, I have successfully followed the tutorial. Then I started to think th
I am working on transfer learning for an image classification task. The training generator is as follows: train_generator = train_datagen.flow_from_directory(
I try to transfer learn a LightningModule. The relevant part of the code is this: class DeepFilteringTransferLearning(pl.LightningModule): def __init__(self
I was curious if it is possible to use transfer learning in text generation, and re-train/pre-train it on a specific kind of text. For example, having a pre