{"product_id":"evolutionary-deep-learning","title":"Evolutionary Deep Learning","description":"\u003cdiv class=\"product-page-section\" style='color: rgb(51, 51, 51); text-transform: none; text-indent: 0px; letter-spacing: normal; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px; font-style: normal; font-weight: 300; margin-bottom: 36px; word-spacing: 0px; display: block; white-space: normal; box-sizing: border-box; orphans: 2; widows: 2; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;'\u003e  \u003cdiv class=\"product-page-section\" style=\"padding-bottom: 0px; margin-bottom: 0px; display: block; box-sizing: border-box;\"\u003e   \u003cb style=\"font-weight: bold; box-sizing: border-box;\"\u003eDiscover one-of-a-kind AI strategies never before seen outside of academic papers! Learn how the principles of evolutionary computation overcome deep learning''s common pitfalls and deliver adaptable model upgrades without constant manual adjustment.\u003c\/b\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003eIn   \u003cspan\u003e \u003c\/span\u003e   \u003ci style=\"box-sizing: border-box;\"\u003eEvolutionary Deep Learning\u003c\/i\u003e   \u003cspan\u003e \u003c\/span\u003eyou will learn how to:   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003cul style=\"padding-left: 17.5px; margin-top: 0px; margin-bottom: 10.5px; box-sizing: border-box;\"\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eSolve complex design and analysis problems with evolutionary computation\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eTune deep learning hyperparameters with evolutionary computation (EC), genetic algorithms, and particle swarm optimization\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eUse unsupervised learning with a deep learning autoencoder to regenerate sample data\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eUnderstand the basics of reinforcement learning and the Q Learning equation\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eApply Q Learning to deep learning to produce deep reinforcement learning\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eOptimize the loss function and network architecture of unsupervised autoencoders\u003c\/li\u003e    \u003cli style=\"box-sizing: border-box;\"\u003eMake an evolutionary agent that can play an OpenAI Gym game\u003c\/li\u003e   \u003c\/ul\u003e   \u003cbr style=\"box-sizing: border-box;\"\u003e   \u003ci style=\"padding-bottom: 0px; margin-bottom: 0px; box-sizing: border-box;\"\u003eEvolutionary Deep Learning\u003c\/i\u003e   \u003cspan\u003e \u003c\/span\u003eis a guide to improving your deep learning models with AutoML enhancements based on the principles of biological evolution. This exciting new approach utilizes lesser-known AI approaches to boost performance without hours of data annotation or model hyperparameter tuning.  \u003c\/div\u003e \u003c\/div\u003e \u003cdiv class=\"product-page-section\" style='color: rgb(51, 51, 51); text-transform: none; text-indent: 0px; letter-spacing: normal; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px; font-style: normal; font-weight: 300; margin-bottom: 36px; word-spacing: 0px; display: block; white-space: normal; box-sizing: border-box; orphans: 2; widows: 2; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;'\u003e  \u003ch2 style='margin: 0px 0px 10px; color: inherit; text-transform: lowercase; line-height: 1.1; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 27px; font-weight: bold; box-sizing: border-box;'\u003eabout the technology\u003c\/h2\u003e  \u003ca name=\"about-the-technology\" class=\"anchor\" style=\"color: rgb(64, 127, 191); padding-bottom: 0px; text-decoration: none; margin-bottom: 0px; display: block; visibility: hidden; position: relative; box-sizing: border-box; background-color: transparent;\"\u003e\u003c\/a\u003eEvolutionary deep learning merges the biology-simulating practices of evolutionary computation (EC) with the neural networks of deep learning. This unique approach can automate entire DL systems and help uncover new strategies and architectures. It gives new and aspiring AI engineers a set of optimization tools that can reliably improve output without demanding an endless churn of new data. \u003c\/div\u003e \u003cdiv class=\"product-page-section\" style='color: rgb(51, 51, 51); text-transform: none; text-indent: 0px; letter-spacing: normal; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px; font-style: normal; font-weight: 300; margin-bottom: 36px; word-spacing: 0px; display: block; white-space: normal; box-sizing: border-box; orphans: 2; widows: 2; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;'\u003e  \u003ch2 style='margin: 0px 0px 10px; color: rgb(51, 51, 51); text-transform: lowercase; line-height: 1.1; text-indent: 0px; letter-spacing: normal; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 27px; font-style: normal; font-weight: bold; word-spacing: 0px; white-space: normal; box-sizing: border-box; orphans: 2; widows: 2; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;'\u003eabout the reader\u003c\/h2\u003e  \u003ca name=\"about-the-reader\" class=\"anchor\" style='color: rgb(64, 127, 191); text-transform: none; text-indent: 0px; letter-spacing: normal; padding-bottom: 0px; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px; font-style: normal; font-weight: 300; text-decoration: none; margin-bottom: 0px; word-spacing: 0px; display: block; white-space: normal; visibility: hidden; position: relative; box-sizing: border-box; orphans: 2; widows: 2; background-color: transparent; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px;'\u003e\u003c\/a\u003e  \u003cspan style='color: rgb(51, 51, 51); text-transform: none; text-indent: 0px; letter-spacing: normal; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px; font-style: normal; font-weight: 300; word-spacing: 0px; float: none; display: inline !important; white-space: normal; orphans: 2; widows: 2; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;'\u003eFor data scientists who know Python.\u003c\/span\u003e \u003c\/div\u003e \u003cdiv class=\"product-page-section\" style='color: rgb(51, 51, 51); text-transform: none; text-indent: 0px; letter-spacing: normal; font-family: Lato, -apple-system, BlinkMacSystemFont, \"avenir next\", avenir, \"helvetica neue\", helvetica, Ubuntu, roboto, noto, \"segoe ui\", arial, sans-serif; font-size: 17.25px; font-style: normal; font-weight: 300; margin-bottom: 36px; word-spacing: 0px; display: block; white-space: normal; box-sizing: border-box; orphans: 2; widows: 2; font-variant-ligatures: normal; font-variant-caps: normal; -webkit-text-stroke-width: 0px; text-decoration-thickness: initial; text-decoration-style: initial; text-decoration-color: initial;'\u003e    \u003c\/div\u003e","brand":"MediaPlace","offers":[{"title":"Default Title","offer_id":57307403747710,"sku":"NW9781617299520","price":63.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1379\/1261\/files\/9781617299520.jpg?v=1778577678","url":"https:\/\/mediaplace.com\/en-usa\/products\/evolutionary-deep-learning","provider":"MediaPlace","version":"1.0","type":"link"}