{"id":269,"date":"2021-08-19T09:00:00","date_gmt":"2021-08-19T05:00:00","guid":{"rendered":"https:\/\/alphonsedevasia.com\/blog\/?p=269"},"modified":"2022-09-03T17:17:01","modified_gmt":"2022-09-03T13:17:01","slug":"deep-playground","status":"publish","type":"post","link":"https:\/\/alphonsedevasia.com\/blog\/deep-playground\/","title":{"rendered":"Deep Playground"},"content":{"rendered":"\n

Deep <\/span><\/a>P<\/span><\/a>layground<\/span><\/a> is an interactive visualization of neural networks, written in TypeScript using d3.js. Tinker with a Neural Network right inside your browser without any coding or additional package installation.<\/p>\n\n\n

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Deep learning using neural network is a technique for building a computer program that learns from data. It is based very loosely on how we think the human brain works. First, a collection of software \u201cneurons\u201d are created and connected together, allowing them to send messages to each other. Next, the network is asked to solve a problem, which it attempts to do over and over, each time strengthening the connections that lead to success and diminishing those that lead to failure.<\/p>\n\n\n\n

Deep playground is open sourced and is available on GitHub<\/span><\/a>.<\/p>\n\n\n\n

Created by Daniel Smilkov & Shan Carter and is a continuation of many people\u2019s previous work \u2014 most notably Andrej Karpathy\u2019s convnet.js demo<\/a> and Chris Olah\u2019s articles<\/a> about neural networks.<\/em><\/p>\n\n\n\n

Books to learn about Deep learning and Neural Networks<\/em><\/p>\n\n\n\n