{"id":3456,"date":"2024-09-01T16:44:53","date_gmt":"2024-09-01T16:44:53","guid":{"rendered":"https:\/\/workhouse.sweetdishy.com\/?p=3456"},"modified":"2024-09-01T16:44:54","modified_gmt":"2024-09-01T16:44:54","slug":"key-takeaways-4","status":"publish","type":"post","link":"https:\/\/workhouse.sweetdishy.com\/index.php\/2024\/09\/01\/key-takeaways-4\/","title":{"rendered":"Key Takeaways"},"content":{"rendered":"\n<ul class=\"wp-block-list\">\n<li>Deep learning, which is a subfield of machine learning, processes huge amounts of data to detect relationships and patterns that humans are often unable to detect. The word \u201cdeep\u201d describes the number of hidden layers.<\/li>\n\n\n\n<li>An artificial neural&nbsp;network&nbsp;(ANN) is a function that includes units that have weights and are used to predict values in an AI model.<\/li>\n\n\n\n<li>A hidden layer is a part of a model that processes incoming data.<\/li>\n\n\n\n<li>A feed-forward neural&nbsp;network&nbsp;has data that goes only from input to the hidden layer to the output. The results do not cycle back. Yet they can go into another neural network.<\/li>\n\n\n\n<li>An&nbsp;activation function&nbsp;is non-linear. In other words, it tends to do a better job of reflecting the real world.<\/li>\n\n\n\n<li>A&nbsp;sigmoid&nbsp;is an&nbsp;activation function&nbsp;that compresses the input value into a range of 0\u20131, which makes it easier for analysis.<\/li>\n\n\n\n<li>Backpropagation&nbsp;is a sophisticated technique to adjust the weights in a neural&nbsp;network. This approach has been critical for the growth in deep learning.<\/li>\n\n\n\n<li>A recurrent neural&nbsp;network&nbsp;(RNN) is a function that not only processes the input but also prior inputs across time.<\/li>\n\n\n\n<li>A convolutional neural&nbsp;network&nbsp;(CNN) analyzes data section by section (that is, by convolutions). This model is geared for complex applications like image recognition.<\/li>\n\n\n\n<li>A generative adversarial&nbsp;network&nbsp;or GAN is where two neural networks compete with each other in a tight feedback loop. The result is often the creation of a new object.<\/li>\n\n\n\n<li>Explainability describes techniques for transparency with complex deep learning models.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":3327,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[442],"tags":[],"class_list":["post-3456","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-deep-learning"],"jetpack_featured_media_url":"https:\/\/workhouse.sweetdishy.com\/wp-content\/uploads\/2024\/08\/deep-learning-1.png","_links":{"self":[{"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/posts\/3456","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/comments?post=3456"}],"version-history":[{"count":1,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/posts\/3456\/revisions"}],"predecessor-version":[{"id":3457,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/posts\/3456\/revisions\/3457"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/media\/3327"}],"wp:attachment":[{"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/media?parent=3456"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/categories?post=3456"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/workhouse.sweetdishy.com\/index.php\/wp-json\/wp\/v2\/tags?post=3456"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}