What is the difference b.t. tf.layers.dense and tf.layers.Dense · Issue #22020 · tensorflow/tensorflow · GitHub
tf.keras and TensorFlow: Batch Normalization to train deep neural networks faster | by Chris Rawles | Towards Data Science
![machine learning - What is the point of having a dense layer in a neural network with no activation function? - Cross Validated machine learning - What is the point of having a dense layer in a neural network with no activation function? - Cross Validated](https://i.stack.imgur.com/R3hsF.png)
machine learning - What is the point of having a dense layer in a neural network with no activation function? - Cross Validated
![tensorflow - Custom loss function in Keras that penalizes output from intermediate layer - Stack Overflow tensorflow - Custom loss function in Keras that penalizes output from intermediate layer - Stack Overflow](https://i.stack.imgur.com/r0SWl.png)
tensorflow - Custom loss function in Keras that penalizes output from intermediate layer - Stack Overflow
![python - tf and tf.keras Dense layer shows completely different behavior in my setup - Stack Overflow python - tf and tf.keras Dense layer shows completely different behavior in my setup - Stack Overflow](https://code.julien.li/so-tf-problem.png)
python - tf and tf.keras Dense layer shows completely different behavior in my setup - Stack Overflow
![python - How to implement a neural network with a not-fully-connected layer as the final layer? - Stack Overflow python - How to implement a neural network with a not-fully-connected layer as the final layer? - Stack Overflow](https://i.stack.imgur.com/Gdpz7.png)
python - How to implement a neural network with a not-fully-connected layer as the final layer? - Stack Overflow
![Graph disconected: transfer-learning model with custom dense layers · Issue #71 · keisen/tf-keras-vis · GitHub Graph disconected: transfer-learning model with custom dense layers · Issue #71 · keisen/tf-keras-vis · GitHub](https://user-images.githubusercontent.com/61247376/126343691-93b14eee-16e4-44de-bf93-50f6b91b580e.png)