{"id":311,"date":"2020-11-10T18:14:35","date_gmt":"2020-11-10T18:14:35","guid":{"rendered":"https:\/\/demosites.io\/nonprofit-gb\/?page_id=311"},"modified":"2020-11-10T18:14:35","modified_gmt":"2020-11-10T18:14:35","slug":"7ca6c-home","status":"publish","type":"page","link":"https:\/\/amysangelsnetwork.com\/","title":{"rendered":"Home"},"content":{"rendered":"\n
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Let’s change the World Together<\/h1>\n\n\n\n

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Our Projects<\/a><\/div>\n\n\n\n
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Our Mission<\/h2>\n\n\n\n

Ray RLlib is the Ray-based library for implementing reinforcement learning applications, supporting all the popular. Live-edge shoreditch prism meggings cornhole adaptogen 3 wolf moon cloud bread truffaut blue bottle. Gastropub neutra literally, hell of austin truffaut irony. Scenester meh coloring book gastropub. Wolf beard organic synth vexillologist. Live-edge sartorial hexagon you probably haven’t heard of them.<\/p>\n<\/div>\n\n\n\n

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Nature Protection<\/h3>\n\n\n\n

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River Preservation<\/h3>\n\n\n\n

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Wildlife Conservation<\/h3>\n\n\n\n

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926,437<\/h1>\n\n\n\n

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How can we change the world?<\/h2>\n\n\n\n
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Ray RLlib is the Ray-based library for implementing reinforcement learning applications, supporting all the popular, state-of-the-art libraries, including integrations with TensorFlow and PyTorch for deep reinforcement learning. This tutorial explains RL principles and common algorithms, including multi-armed bandits, using a series of example problems.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Our Mission Ray RLlib is the Ray-based library for implementing reinforcement learning applications, supporting all the popular. Live-edge shoreditch prism meggings cornhole adaptogen 3 wolf moon cloud bread truffaut blue bottle. Gastropub neutra literally, hell of austin truffaut irony. Scenester meh coloring book gastropub. Wolf beard organic synth vexillologist. Live-edge sartorial hexagon you probably haven’t… Read More »Home<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"neve_meta_sidebar":"full-width","neve_meta_container":"","neve_meta_enable_content_width":"on","neve_meta_content_width":100,"neve_meta_title_alignment":"","neve_meta_author_avatar":"","neve_post_elements_order":"","neve_meta_disable_header":"","neve_meta_disable_footer":"","neve_meta_disable_title":"on","_themeisle_gutenberg_block_has_review":false,"footnotes":""},"class_list":["post-311","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/pages\/311","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/comments?post=311"}],"version-history":[{"count":0,"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/pages\/311\/revisions"}],"wp:attachment":[{"href":"https:\/\/amysangelsnetwork.com\/index.php\/wp-json\/wp\/v2\/media?parent=311"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}