Training & Testing the modified neural network
Course Content
0 / 25 completedOverview of the course
Interpolation (or regression) - The fundamental principle of machine learning
From interpolation to neural networks
[Project 1] Most simple neural network Sum of two numbers
What are neural networks
Prepare the training and testing data
Initialize the weights & Calculate the output
Accuracy & Error functions
Gradient of the error function
Using the trained network on the test data
Training the neural network via gradient descent
[Project 2] Complete neural network Sign of the sum of two numbers
Modify input, output & weights
Add an activation function to the neural network
Modify accuracy and error functions
Modify gradient of the error function
Training & Testing the modified neural network
[Project 3] Same neural network Applied to recognize hand-written digits
Apply our neural network to the new problem Number recognition
Improve the gradient function
Analysis of the trained neural network
How to improve the network
Outlook Pretrained neural networks & Machine learning in Wolfram Mathematica
Goodbye!
[Installation] Python and Jupyter Notebook via Anaconda