Neural Networks in Python from Scratch: Learning by Doing

** The quickest way to understanding (and programming) neural networks using Python **This course is for everyone who wants to learn how neural networks work by hands-on programming. Everybody is talking about neural networks but they are hard to understand without setting one up yourself. Luckily, the mathematics and programming skills (python) required are on a basic level so we can progam 3 neural networks in just over 3 hours.

Do not waste your time. This course is optimized to give you the deepest insight into this fascinating topic in the shortest amount of time possible. The focus is fully on learning-by-doing and I only introduce new concepts once they are needed.

What you will learnAfter a short introduction, the course is separated into three segments - 1 hour each:1) Set-up the most simple neural network: Calculate the sum of two numbers. You will learn about:Neural network architectureWeights, input & output layerTraining & test dataAccuracy & error functionFeed-forward & back-propagationGradient descent2) We modify this network: Determine the sign of the sum. You will be introduced to:Hidden layersActivation functionCategorization3) Our network can be applied to all sorts of problems, like image recognition: Determine hand-written digits.

After this cool and useful real-life application, I will give you an outlook:How to improve the networkWhat other problems can be solved with neural networks. How to use pre-trained networks without much effortWhy me. My name is Börge Göbel and I am a postdoc working as a scientist in theoretical physics where neural networks are used a lot.