Current location - Education and Training Encyclopedia - Education and training - What does deep learning learn specifically?
What does deep learning learn specifically?
Deep learning includes neural network, BP back propagation algorithm, TensorFlow deep learning tool and so on.

Neural networks need to learn:

From biological neurons to artificial neurons

Activate functions Relu, Tanh, Sigmoid.

Understanding logistic regression classification through neural network topology

Understanding Softmax regression classification through neural network topology

Solving the problem of upgrading and dimensionality reduction through neural network hidden stratification

The reason why the activation function of hidden layer must be nonlinear is analyzed

Application of neural network in sklearn module

Case study on cement strength prediction and drawing neural network topology

BP back propagation algorithm needs to learn:

BP reverse propagation purpose

Chain derivative rule

BP back propagation derivation

Application of Different Activation Functions in Back Propagation

Application of Different Loss Functions in Back Propagation

Python realizes the actual combat case of neural network

TensorFlow deep learning tools are designed to:

TF installation (including CUDA and cudnn installation)

TF realized the analytical solution of multiple linear regression.

TF realizes the gradient descent solution of multiple linear regression

TF forecast California housing price case

TF realizes Softmax regression.

Case study of MNIST handwritten numeral recognition project

Save and load TF framework model

8) TF has realized DNN multilayer neural network.

9) DNN classification MNIST handwritten numeral recognition project case

10) tensor board module visualization

These are some knowledge involved in deep learning. Generally speaking, it is necessary to deeply understand the neural network algorithm and its optimization algorithm, master the TensorFlow development process, and complete the regression and classification tasks by implementing neural networks. TensorFlow framework is easy to learn, and other deep learning frameworks such as Keras and PyTorch are easy to master. In addition, you can do some actual combat, so that you can be more skilled.