Neural Network Playground: Try it Yourself!How do you design a deep learning network?
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This is an extremely complicated process which depends on the particular AI model used and the task requested of the network. It is a task truly left for experts, but if you want to gain further insight into the process, a detailed self-paced and free educational course (all the way from basic concepts to programming in Python) is available at https://ai.google/education.
The example below is part of the Google "Playground", allowing the visitor to create simple neural networks for solving simple problems, like regression and classification. Click on the image below to be taken to the site directly.
Google "Playground" for Machine Learning. Click imge to open link in new window.
Here are some notes to guide you using this neural network simulator that initially contains two hidden layers and with the goal of classifying data points as blue or orange based on their coordinates:
- Push the play button (arrow) to get a sense of what happens during the training process.
- You will see that after about 50 training sessions (epochs), the neural network has self-adjusted its weights and biases on each neuron to allow successful classification of the data.
- Note how the output from each neuron changes during the training process as a result of back-propagation.
- You can play around by changing multiple parameters such as using different activation functions, numbers of hidden layers, and number of neurons in each layer.
- You can also change the problem to Linear Regression from Classification.
- Have fun!
References
Chartrand G, Cheng PM, Vorontsov E, et al. Deep learning: a primer for radiologists. RadioGraphics 2017; 37:2113-2131. [DOI LINK]
Google Developers. Machine learning glossary. (Downloaded from https://ai.google/education 28 July 2022).
Nicholson C. A beginner’s guide to neural networks and deep learning. In: A.I. Wiki. A beginner’s guide to important topics in AI, machine learning, and deep learning. (Downloaded from wiki.pathmind.com 13 Jan 2022)
Chartrand G, Cheng PM, Vorontsov E, et al. Deep learning: a primer for radiologists. RadioGraphics 2017; 37:2113-2131. [DOI LINK]
Google Developers. Machine learning glossary. (Downloaded from https://ai.google/education 28 July 2022).
Nicholson C. A beginner’s guide to neural networks and deep learning. In: A.I. Wiki. A beginner’s guide to important topics in AI, machine learning, and deep learning. (Downloaded from wiki.pathmind.com 13 Jan 2022)
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