Link to the previous post : https://course.dvanalyticsmds.com/204-5-6-neural-network-intuition/
In all the previous posts we progressed to this part. We will breakdown the steps how a neural network starts and ends.
The Neural Network Algorithm
- Step 1: Initialization of weights: Randomly select some weights.
- Step 2 : Training & Activation: Input the training values and perform the calculations forward.
- Step 3 : Error Calculation: Calculate the error at the outputs. Use the output error to calculate error fractions at each hidden layer.
- Step 4: Weight training: Update the weights to reduce the error, recalculate and repeat the process of training & updating the weights for all the examples.
- Step 5: Stopping criteria: Stop the training and weights updating process when the minimum error criteria is met.
Randomly Initialize Weights
Training & Activation
Error Calculation at Output
Error Calculation at hidden layers
Calculate weight corrections
Update Weights
Stopping Criteria
The next post is a demo on neural network algorithm. Link to the next post : https://course.dvanalyticsmds.com/204-5-8-neural-network-algorithm-demo/
