rouseguy / Deeplearning Image
Licence: mit
Introduction to Deep Learning for Image Recognition
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Introduction to Deep Learning for Image Recognition
This notebook accompanies the Introduction to Deep Learning for Image Recognition workshop to explain the core concepts of deep learning with emphasis on classifying images as the application. Python data stack is used for the workshop.
Overview
The following topics are covered
- What is deep learning?
- Motivation: Some use cases
- Building blocks of Neural Networks (Neuron, Activation Function, Backpropagation Algorithm)
- Introduction to the problem : MNIST dataset
- Building neural network from scratch
- Introduction to
keras - Multi-layer perceptron
- Convolutional Neural Network
Depending on time, the following topics might be covered
- Using
tensorflowas backend forkeras - Unsupervised learning using Autoencoders
Installation Instructions
Please refer to the installation instructions document. That document also has instructions on how to run a script to check if the required packages are installed.
Slides
The slides used for the workshop are available here
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