Introduction to Keras Transfer Learning (9.1)

preview_player
Показать описание
Transfer learning is a process that loads weights from previously trained neural networks. This video shows you how to train a neural network and transfer its weights to another.

Code for This Video:

Follow Me/Subscribe:

  1. Jeff Heaton
  2. python
  3. python introduction
  4. python introduction deep learning
  5. deep learning
  6. neural network
Рекомендации по теме
Introduction to Keras 0:10:33

Introduction to Keras Transfer Learning (9.1)

Introduction to Keras 0:09:00

Introduction to Keras Transfer Learning (9.1)

Transfer Learning | 0:25:55

Transfer Learning | Deep Learning Tutorial 27 (Tensorflow, Keras & Python)

What is Transfer 0:10:52

What is Transfer Learning? | With code in Keras

Keras with TensorFlow 2:47:55

Keras with TensorFlow Course - Python Deep Learning and Neural Networks for Beginners Tutorial

What is Transfer 0:33:53

What is Transfer Learning? Transfer Learning in Keras | Fine Tuning Vs Feature Extraction

Transfer Learning with 0:29:22

Transfer Learning with Keras and TensorFlow: How to Fine-Tune a Pretrained Neural Network

Transfer Learning for 0:05:43

Transfer Learning for Languages and Keras (9.4)

Transfer Learning, Fine-Tuning 0:18:46

Transfer Learning, Fine-Tuning ResNet50 || CNN || Image Classification || Deep Learning || AI

Transfer Learning with 0:00:57

Transfer Learning with Keras and Tensorflow

Transfer Learning for 0:03:35

Transfer Learning for Keras Feature Engineering (9.5)

Transfer Learning for 0:11:33

Transfer Learning for Computer Vision and Keras (9.3)

Transfer Learning Using 0:12:36

Transfer Learning Using CNN(VGG 16)| Keras Tutorial|

Keras VGG16 Transfer 0:00:50

Keras VGG16 Transfer learning for classifications

Keras introduction 0:02:51

Keras introduction

3.3 Apply Fine 0:06:53

3.3 Apply Fine Tuning/Transfer Learning very easily on Keras - Pt.1

Transfer Learning with 0:21:20

Transfer Learning with Keras

Introduction | Deep 0:03:39

Introduction | Deep Learning Tutorial 1 (Tensorflow Tutorial, Keras & Python)

Keras Transfer Learning 0:08:06

Keras Transfer Learning for NLP (9.3)

Transfer Learning using 0:08:43

Transfer Learning using Pre-trained model | Keras example

Transfer Learning with 0:13:33

Transfer Learning with Keras & TensorFlow

Advanced Deep Learning 0:05:26

Advanced Deep Learning with Keras: Introduction to Neural Style Transfer | packtpub.com

What is BERT? 0:23:03

What is BERT? | Deep Learning Tutorial 46 (Tensorflow, Keras & Python)

Keras Transfer Learning 0:10:46

Keras Transfer Learning for Computer Vision (9.2)

Комментарии
Автор

Transfer learning? Professor, this course is really HEATon up! Thank you for sharing your time and knowledge with us all :)

Zzznmop
Автор

a very crisp and clear explanation of what other tutorials has been trying to explain over pages (y)

roshneekishore
Автор

Hello Jeff, I am trying to add more data to already trained model, i have a 4 class model, my goal is to add data to the model to learn as I get the data, my model size before training with new data was 90 MB, i tried the same steps as yours but my model size got shrunk to 34 MB and it's not predicting properly. I am thinking my previous weights are some how lost, can you please guide ?
new_model = load_model('my_model2.h5')
model3 = Sequential()
for i in range(7):
layer = new_model.layers[i]
layer.trainable = False
model3.add(layer)
model3.add(Dense(512))

model3.add(Dropout(0.3))
model3.add(Dense((num_labels), activation='softmax'))
model3.layers[-4].name = 'dense_7'
model3.layers[-1].name = 'dense_8'
model3.layers[-2].name = 'dropout_3'
model3.layers[-3].name = 'activation_3'
model3.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])
model3.fit(x_train, y_train, batch_size = batch_size, epochs = 50, verbose = 1)
model3.summary()

deepakec