Blog

• Oct 6, 2021

  9. The Activation Layer

  Let us see the neural structure for the Activation layer.
• Sep 19, 2021

  8. The Linear Layer

  We explore the Linear layer. It is the first step to be able to design deep learning models. We also speak about the neural structure and a better way to compute the backward pass.
• Aug 24, 2021

  7. Batch Learning

  A new idea to build a more robust learning: learn on multiple data input at once.
• Aug 23, 2021

  6. The Gradient Descent Algorithm

  We use the different parts we have seen so far to run the training phase from scratch.
• Aug 19, 2021

  5. The Weights

  The weights are the learning elements of the deep learning model: the core of the learning process.
• Aug 14, 2021

  4. The Backward Pass

  The backward pass is the nemesis of the forward pass: this is the second step toward the learning process.
• Aug 9, 2021

  3. The Loss function

  We complete the deep learning model with the loss function: this is the first step toward the learning process.