Machine learning in practice: how machine learning works in data-driven research{"id":5755,"date":"2023-07-28T10:10:06","date_gmt":"2023-07-28T10:10:06","guid":{"rendered":"https:\/\/roulottemagazine.com\/?p=5755"},"modified":"2023-09-23T11:31:53","modified_gmt":"2023-09-23T11:31:53","slug":"machine-learning-in-practice-how-machine-learning","status":"publish","type":"post","link":"https:\/\/roulottemagazine.com\/CA\/2023\/07\/machine-learning-in-practice-how-machine-learning\/","title":{"rendered":"Machine learning in practice: how machine learning works in data-driven research"},"content":{"rendered":"<p><h1>What is Supervised Machine Learning ? How it Works Examples<\/h1>\n<\/p>\n<p><img class='wp-post-image' style='display: block;margin-left:auto;margin-right:auto;' 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\" width=\"306px\" alt=\"how machine learning works\"\/><\/p>\n<p><p>Sometimes developers will synthesize data from a machine learning model, while data scientists will contribute to developing solutions for the end user. Collaboration between these two disciplines can make ML projects more valuable and useful. The training data given to a machine in supervised machine learning acts as the controller. For instance, you give a machine learning algorithm the right answer to the question while it is learning.<\/p>\n<\/p>\n<div style='border: black dotted 1px;padding: 13px;'>\n<h3>U.S. Copyright Office Ponders Copyright Protection for AI-Generated &#8230; &#8211; Clark Hill<\/h3>\n<p>U.S. Copyright Office Ponders Copyright Protection for AI-Generated &#8230;.<\/p>\n<p>Posted: Wed, 13 Sep 2023 19:53:05 GMT [<a href='https:\/\/news.google.com\/rss\/articles\/CBMimwFodHRwczovL3d3dy5jbGFya2hpbGwuY29tL25ld3MtZXZlbnRzL25ld3MvdS1zLWNvcHlyaWdodC1vZmZpY2UtcG9uZGVycy1jb3B5cmlnaHQtcHJvdGVjdGlvbi1mb3ItYWktZ2VuZXJhdGVkLXdvcmtzLWZvbGxvd2luZy1kLWMtY2lyY3VpdHMtdGhhbGVyLWRlY2lzaW9uL9IBAA?oc=5' rel=\"nofollow\">source<\/a>]<\/p>\n<\/div>\n<p><p>Finally, once all testing and evaluation has been completed it is possible to deploy a successful machine learning system into production so that it can be utilized for its intended purpose. By doing this developers can ensure that their machine learning system is operating at peak efficiency and that no unexpected errors arise during its use. In conclusion, testing <a href=\"https:\/\/www.metadialog.com\/\">https:\/\/www.metadialog.com\/<\/a> and evaluating performance plays an important role in ensuring optimal performance from a Machine Learning system throughout its lifetime in production applications. Machine Learning has an extensive range of applications in various fields, including natural language processing, computer vision, recommendation systems, finance, healthcare, and many more.<\/p>\n<\/p>\n<p><h2>Why machine learning helps humans to learn<\/h2>\n<\/p>\n<p><p>Machine learning will be used to power many of these devices, and we\u2019ll be taking a closer look at that throughout the rest of this article. For example, Netflix uses it to crunch the <a href=\"https:\/\/www.metadialog.com\/blog\/how-does-ml-work\/\">how machine learning works<\/a> numbers and to make  recommendations  based on what other similar users have enjoyed. Machine learning is used in all sorts of different industries, from healthcare to urban planning.<\/p>\n<\/p>\n<p><img class='aligncenter' style='display: block;margin-left:auto;margin-right:auto;' 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\" width=\"301px\" alt=\"how machine learning works\"\/><\/p>\n<p><p>AI \u2013 a significant branch of machine intelligence, it encompasses the way in which tech works overall in an intelligent fashion to behave and react like humans. Dive in for free with a 10-day trial of the O\u2019Reilly learning platform\u2014then explore all the other resources our members count on to build skills and solve problems every day. Take O\u2019Reilly with you and learn anywhere, anytime on your phone and tablet. 6 The prepare_country_stats() function\u2019s definition is not shown here (see this chapter\u2019s Jupyter notebook if you want all the gory details). It\u2019s just boring Pandas code that joins the life satisfaction data from the OECD with the GDP per capita data from the IMF.<\/p>\n<\/p>\n<p><h2>Using MS Teams to address a new learning culture<\/h2>\n<\/p>\n<p><p>This type of learning is great for clustering (Are these spells offensive or defensive?) and anomaly detection (Does this spell belong in this book?). If there\u2019s one thing us Lolly elves do well, it\u2019s machine learning.When it comes to what your business needs, we have the expertise and top-tier development team to accelerate your business with machine learning. You won\u2019t find any other tech-wizards in the tech realm willing <a href=\"https:\/\/www.metadialog.com\/blog\/how-does-ml-work\/\">how machine learning works<\/a> to offer up advanced secrets such as ours.Don&#8217;t believe us? Just check out our machine learning development reviews from like-minded sorcerers and shamans to see how we can move your project forward. Through the intricate dance of code, we engineer models that learn from your business data, banishing mundane tasks and predicting future trends. We\u2019re not just coding; we&#8217;re conjuring growth, transformation, and success.<\/p>\n<\/p>\n<ul>\n<li>Once you upload all your family photos to the service, it automatically recognizes that the same person A shows up in photos 1, 5, and 11, while another person B shows up in photos 2, 5, and 7.<\/li>\n<li>Without data science, machine learning algorithms won\u2019t work as they train on datasets.<\/li>\n<li>As a very simple example, you might draw points in the figure above &#8220;out of your screen&#8221; into the third dimension by a distance that corresponds to their original distance to the point .<\/li>\n<li>AI technologies include natural language processing, machine learning, robotics, deep learning, computer vision and more.<\/li>\n<\/ul>\n<div itemScope itemProp=\"mainEntity\" itemType=\"https:\/\/schema.org\/Question\">\n<div itemProp=\"name\">\n<h2>Is SQL used in machine learning?<\/h2>\n<\/div>\n<div itemScope itemProp=\"acceptedAnswer\" itemType=\"https:\/\/schema.org\/Answer\">\n<div itemProp=\"text\">\n<p>Machine Learning Services is a feature in SQL Server that gives the ability to run Python and R scripts with relational data. You can use open-source packages and frameworks, and the Microsoft Python and R packages, for predictive analytics and machine learning.<\/p>\n<\/div><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[68],"tags":[],"_links":{"self":[{"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/posts\/5755"}],"collection":[{"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/comments?post=5755"}],"version-history":[{"count":1,"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/posts\/5755\/revisions"}],"predecessor-version":[{"id":5756,"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/posts\/5755\/revisions\/5756"}],"wp:attachment":[{"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/media?parent=5755"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/categories?post=5755"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/roulottemagazine.com\/wp-json\/wp\/v2\/tags?post=5755"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}