{"id":1980,"date":"2019-09-27T05:33:11","date_gmt":"2019-09-27T05:33:11","guid":{"rendered":"http:\/\/kusuaks7\/?p=1585"},"modified":"2024-03-20T12:19:32","modified_gmt":"2024-03-20T12:19:32","slug":"state-of-ai-and-machine-learning-in-2019","status":"publish","type":"post","link":"https:\/\/www.experfy.com\/blog\/ai-ml\/state-of-ai-and-machine-learning-in-2019\/","title":{"rendered":"State Of AI And Machine Learning In 2019"},"content":{"rendered":"\t\t<div data-elementor-type=\"wp-post\" data-elementor-id=\"1980\" class=\"elementor elementor-1980\" data-elementor-post-type=\"post\">\n\t\t\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-656e8900 elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"656e8900\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-610218c3\" data-id=\"610218c3\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-67347558 elementor-widget elementor-widget-text-editor\" data-id=\"67347558\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li>Marketing and Sales prioritize AI and machine learning higher than any other department in enterprises today.<\/li>\n \t<li>In-memory analytics and in-database analytics are the most important to Finance, Marketing, and Sales when it comes to scaling their AI and machine learning modeling and development efforts.<\/li>\n \t<li>R&amp;D\u2019s adoption of AI and machine learning is the fastest of all enterprise departments in 2019.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-77eb040 elementor-widget elementor-widget-text-editor\" data-id=\"77eb040\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\tThese and many other fascinating insights are from\u00a0<a href=\"http:\/\/dresneradvisory.com\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:http:\/\/dresneradvisory.com\/\">Dresner Advisory Services\u2019<\/a>6<sup>th<\/sup>\u00a0annual\u00a0<a href=\"https:\/\/gumroad.com\/l\/dTfno\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:https:\/\/gumroad.com\/l\/dTfno\">2019 Data Science and Machine Learning Market Study<\/a>\u00a0(client access reqd) published last month. The study found that advanced initiatives related to data science and machine learning, including data mining, advanced algorithms, and predictive analytics are ranked the 8th priority among the 37 technologies and initiatives surveyed in the study. Please see\u00a0<a href=\"https:\/\/gumroad.com\/l\/dTfno\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:https:\/\/gumroad.com\/l\/dTfno\">page 12 of the survey<\/a>\u00a0for an overview of the methodology.\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-144b3d1 elementor-widget elementor-widget-text-editor\" data-id=\"144b3d1\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\u201cThe Data Science and Machine Learning Market Study is a progression of our analysis of this market which began in 2014 as an examination of advanced and predictive analytics,\u201d said\u00a0<a href=\"https:\/\/www.linkedin.com\/in\/howarddresner\/\" target=\"_blank\" rel=\"nofollow noopener noreferrer\" data-ga-track=\"ExternalLink:https:\/\/www.linkedin.com\/in\/howarddresner\/\">Howard Dresner, founder, and chief research officer at Dresner Advisory Services<\/a>. \u201cSince that time, we have expanded our coverage to reflect changes in sentiment and adoption, and have added new criteria, including a section covering neural networks.\u201d\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-08878cd elementor-widget elementor-widget-heading\" data-id=\"08878cd\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"heading.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t<h3 class=\"elementor-heading-title elementor-size-default\"><h3>Key insights from the study include the following:<\/h3><\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<section class=\"has_eae_slider elementor-section elementor-top-section elementor-element elementor-element-410498b elementor-section-boxed elementor-section-height-default elementor-section-height-default\" data-id=\"410498b\" data-element_type=\"section\" data-e-type=\"section\">\n\t\t\t\t\t\t<div class=\"elementor-container elementor-column-gap-default\">\n\t\t\t\t\t<div class=\"has_eae_slider elementor-column elementor-col-100 elementor-top-column elementor-element elementor-element-88184cf\" data-id=\"88184cf\" data-element_type=\"column\" data-e-type=\"column\">\n\t\t\t<div class=\"elementor-widget-wrap elementor-element-populated\">\n\t\t\t\t\t\t<div class=\"elementor-element elementor-element-0c2e42f elementor-widget elementor-widget-text-editor\" data-id=\"0c2e42f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li><strong>Data mining, advanced algorithms, and predictive analytics are among the highest-priority projects for enterprises adopting AI and machine learning in 2019.<\/strong>\u00a0Reporting, dashboards, data integration, and advanced visualization are the leading technologies and initiatives strategic to Business Intelligence (BI) today. Cognitive BI (artificial-intelligence-based BI) ranks comparatively lower at 27th among priorities. The following graphic prioritizes the 27 technologies and initiatives strategic to business intelligence:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-c661aff elementor-widget elementor-widget-image\" data-id=\"c661aff\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2019\/09\/tech-initiatives-strategic-to-BI.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-32044b5 elementor-widget elementor-widget-text-editor\" data-id=\"32044b5\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li><strong>40% of Marketing and Sales teams say data science encompassing AI and machine learning is critical to their success as a department.<\/strong>\u00a0Marketing and Sales lead all departments in how significant they see AI and machine learning to pursue and accomplish their growth goals. Business Intelligence Competency Centers (BICC), R&amp;D, and executive management audiences are the next most interested, and all top four roles cited carry comparable high combined &#8220;critical&#8221; and &#8220;very important&#8221; scores above 60%. The following graphic compares the importance levels by department for data science, including AI and machine learning:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-a1e341d elementor-widget elementor-widget-text-editor\" data-id=\"a1e341d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\n<ul>\n \t<li><strong>R&amp;D, Marketing, and Sales\u2019 high level of shared interest across multiple feature areas reflect combined efforts to define new revenue growth models using AI and machine learning.<\/strong>\u00a0Marketing, Sales, R&amp;D, and the Business Intelligence Competency Centers (BICC) respondents report the most significant interest in having a range of regression models to work with in AI and machine learning applications. Marketing and Sales are also most interested in the next three top features, including hierarchical clustering, textbook statistical functions, and having a recommendation engine included in the applications and platforms they purchase. Dresner\u2019s research team believes that the high shared interest in multiple features areas by R&amp;D, Marketing and Sales is leading indicator enterprises are preparing to pilot AI and machine learning-based strategies to improve customer experiences and drive revenue. The following graphic compares interest and probable adoption by functional area of the enterprises interviewed:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e22215e elementor-widget elementor-widget-image\" data-id=\"e22215e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2019\/09\/AI-and-machine-learning-features-by-functional-area-spider-graphic.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e45c607 elementor-widget elementor-widget-text-editor\" data-id=\"e45c607\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\n<ul>\n \t<li><strong>70% of R&amp;D departments and teams are most likely to adopt data science, AI, and machine learning, leading all functions in an enterprise.<\/strong>\u00a0Dresner\u2019s research team sees the high level of interest by R&amp;D teams as a leading indicator of broader enterprise adoption in the future. The study found 33% of all enterprises interviewed have adopted AI and machine learning, with the majority of enterprises having up to 25 models. Marketing &amp; Sales lead all departments in their current evaluation of data science and machine learning software.<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-3c91bea elementor-widget elementor-widget-image\" data-id=\"3c91bea\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2019\/09\/Deployment-by-functional-area.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-4e8453d elementor-widget elementor-widget-text-editor\" data-id=\"4e8453d\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li><strong>Financial Services &amp; Insurance, Healthcare, and Retail\/Wholesale say data science, AI, and machine learning are critical to their succeeding in their respective industries.<\/strong>\u00a027% of Financial Services &amp; Insurance, 25% of Healthcare and 24% of Retail\/Wholesale enterprises say data science, AI, and machine learning are critical to their success. Less than 10% of Educational institutions consider AI and machine learning vital to their success. The following graphic compares the importance of data science, AI, and machine learning by industry:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-9699223 elementor-widget elementor-widget-image\" data-id=\"9699223\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/thumbor.forbes.com\/thumbor\/960x0\/https%3A%2F%2Fblogs-images.forbes.com%2Flouiscolumbus%2Ffiles%2F2019%2F09%2Fimportance-of-data-science-and-ML-by-industry.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-7bd7c04 elementor-widget elementor-widget-text-editor\" data-id=\"7bd7c04\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\n<ul>\n \t<li><strong>The Telecommunications industry leads all others in interest and adoption of recommendation engines and model management governance.<\/strong>\u00a0The Telecommunications, Financial Services, and Technology industries have the highest level of interest in adopting a range of regression models and hierarchical clustering across all industry respondent groups interviewed. Healthcare respondents have much lower interest in these latter features but high interest in Bayesian methods and text analytics functions. Retail\/Wholesale respondents are often least interested in analytical features. The following graphic compares industries by their level of interest and potential adoption of analytical features in data science, AI, and machine learning applications and platforms:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-17b2346 elementor-widget elementor-widget-image\" data-id=\"17b2346\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/thumbor.forbes.com\/thumbor\/960x0\/https%3A%2F%2Fblogs-images.forbes.com%2Flouiscolumbus%2Ffiles%2F2019%2F09%2FAnalytical-Features-for-Data-Science-and-Machine-Learning-by-Industry.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-5d8fc2f elementor-widget elementor-widget-text-editor\" data-id=\"5d8fc2f\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li><strong>Support for a broad range of regression models, hierarchical clustering, and commonly used textbook statistical functions are the top features enterprises need in data science and machine learning platforms.<\/strong>\u00a0Dresner\u2019s research team found these three features are considered the most important or \u201cmust-have\u201d when enterprises are evaluating data science, AI and machine learning applications and platforms. All enterprises surveyed also expect any data science application or platform they are evaluating to have a recommendation engine included and model management and governance. The following graphic prioritizes the most and least essential features enterprises expect to see in data science, AI, and machine learning software and platforms:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-036afa3 elementor-widget elementor-widget-image\" data-id=\"036afa3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/thumbor.forbes.com\/thumbor\/960x0\/https%3A%2F%2Fblogs-images.forbes.com%2Flouiscolumbus%2Ffiles%2F2019%2F09%2Ffeatures-needed-in-data-science-and-machine-learning.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-e41412e elementor-widget elementor-widget-text-editor\" data-id=\"e41412e\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t<ul>\n \t<li><strong>The top three usability features enterprises are prioritizing today include support for easy iteration of models, access to advanced analytics, and an initiative, simple process for continuous modification of models.<\/strong>\u00a0Support and guidance in preparing analytical data models and fast cycle time for analysis with data preparation are among the highest- priority usability features enterprises expect to see in AI and machine learning applications and platforms. It\u2019s interesting to see the usability attribute of a specialist not required to create analytical models, test and run them at the lower end of the usability rankings. Many AI and machine learning software vendors rely on not needing a specialist to use their applications as a differentiator when the majority of enterprises value \u00a0support for easy iteration of models at a higher level as the graphic below shows:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-54a8b4c elementor-widget elementor-widget-image\" data-id=\"54a8b4c\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2019\/09\/Usability-for-Data-Science-and-Machine-Learning-2014-2019.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-40031f3 elementor-widget elementor-widget-text-editor\" data-id=\"40031f3\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"text-editor.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\n<ul>\n \t<li><strong>2019 is a record year for enterprises\u2019 interest in data science, AI, and machine learning features they perceive as the most needed to achieve their business strategies and goals.<\/strong>\u00a0Enterprises most expect AI and machine learning applications and platforms to support a range of regression models, followed by hierarchical clustering and textbook statistical functions for descriptive statistics. Recommendation engines are growing in popularity as interest grew to at least a tie as the second most important feature to respondents in 2019. Geospatial analysis and Bayesian methods were flat or slightly less important compared to 2018. The following graphic compares six years of interest in data science, AI, and machine learning techniques:<\/li>\n<\/ul>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<div class=\"elementor-element elementor-element-106c130 elementor-widget elementor-widget-image\" data-id=\"106c130\" data-element_type=\"widget\" data-e-type=\"widget\" data-widget_type=\"image.default\">\n\t\t\t\t<div class=\"elementor-widget-container\">\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<img decoding=\"async\" src=\"https:\/\/blogs-images.forbes.com\/louiscolumbus\/files\/2019\/09\/Data-science-AI-machine-learning-feature-time-series-analysis.jpg\" alt=\"\" \/>\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"<p>Marketing and Sales prioritize AI and machine learning higher than any other department in enterprises today. In-memory analytics and in-database analytics are the most important to Finance, Marketing, and Sales when it comes to scaling their AI and machine learning modeling and development efforts. R&amp;D\u2019s adoption of AI and machine learning is the fastest of<\/p>\n","protected":false},"author":138,"featured_media":4087,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"content-type":"","footnotes":""},"categories":[183],"tags":[97],"ppma_author":[2679],"class_list":["post-1980","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-ml","tag-artificial-intelligence"],"authors":[{"term_id":2679,"user_id":138,"is_guest":0,"slug":"louis-columbus","display_name":"Louis Columbus","avatar_url":"https:\/\/www.experfy.com\/blog\/wp-content\/uploads\/2020\/04\/medium_65812956-54d2-4b01-9e05-0d23abb284c7-150x150.jpg","user_url":"https:\/\/softwarestrategiesblog.com\/","last_name":"Columbus","first_name":"Louis","job_title":"","description":"Louis Columbus is currently serving as Principal, IQMS. He is Marketing and Product Management Leader, Forbes Columnist, Software Expertise in Analytics, Cloud, CPQ &amp; ERP Solutions. He teaches MBA courses in international business, global competitive strategies, international market research, and capstone courses in strategic planning and market research. He has taught at California State University, Fullerton: University of California, Irvine; Marymount University, and Webster University."}],"_links":{"self":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/1980","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/users\/138"}],"replies":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/comments?post=1980"}],"version-history":[{"count":4,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/1980\/revisions"}],"predecessor-version":[{"id":36490,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/posts\/1980\/revisions\/36490"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media\/4087"}],"wp:attachment":[{"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/media?parent=1980"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/categories?post=1980"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/tags?post=1980"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/www.experfy.com\/blog\/wp-json\/wp\/v2\/ppma_author?post=1980"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}