Build neural networks with python from scratch

Target audience

Students who especially benefit from this course:

• Are developers who want to learn the mechanics of neural networks
• Want to avoid using neural network libraries and frameworks
• Use frameworks and libraries but want to learn the meaning of the individual network parameters

Training contents

• Neural Network Introduction: What is a neural network?
• Linear Regression: Cost functions and Bias
• Real Data: Second input, Normalize data
• Classification: Gradient descent, Classification strategy, Activation
• Multi-class classification: Softmax, Non-linear data
• Hidden Layers: Adding hidden layers, Random weights
• Handwritten Digits Recognition: Mini batch gradient descent, Digits Dataset

What can you do after this course?

• You understand neural network concepts and ideas, like back propagation and gradient descent
• You are able to build a neural network in any programming language of choice, without the help of frameworks and libraries
• You understand how to better configure the network by plugging in different cost functions and adding hidden layers

Details