{"id":11217,"date":"2022-07-13T09:06:02","date_gmt":"2022-07-13T08:06:02","guid":{"rendered":"https:\/\/ee.yelkdev.site\/?p=11217"},"modified":"2024-12-10T02:17:53","modified_gmt":"2024-12-10T02:17:53","slug":"challenges-in-operationalising-mlops","status":"publish","type":"post","link":"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/","title":{"rendered":"What do practitioners see as the main challenges in Operationalising Machine Learning solutions?"},"content":{"rendered":"

Earlier this year, some of our experts from the data service gave a talk for Data Idols<\/a> on our experiences working with data scientists to move machine learning models into operations.<\/p>\n

The audience was largely data scientists from lots of organisations (mostly not Equal Experts), and so we took the opportunity to find out what their concerns were with a simple survey question: What do you see as the main challenges with machine learning? There were around 100 attendees and people could vote for as many of the challenges as they wanted.<\/p>\n

You can see the results in the chart here:<\/p>\n\"\"\n

Machine Learning experts do not generally see the development of the model as the difficult bit. I suspect that in fact this is the part they love best about the job.\u00a0 Also, most data specialists are familiar with the right techniques for different modeling problems and I think love the data exploration and feature engineering tasks.<\/p>\n

Where they have the most challenges are in integrating a validated model into business operations and managing it once it’s there. We know this is a non-trivial job – and data scientists usually need support from other technical functions.\u00a0 Our MLOps playbook <\/a>was developed to help practitioners understand and address the different aspects of operationalising Machine Learning models.<\/p>\n

The other area where they had most challenges is in accessing data. Since machine learning is fundamentally dependent on data,\u00a0 this is no surprise. Our\u00a0 data pipeline playbook<\/a> was created to help data professionals create reliable access to data sources – it is certainly essential to put some of the practices in place for production models.<\/p>\n","protected":false},"excerpt":{"rendered":"

Find out what data scientists answered when asked the question, \u201cWhat do you see as the main challenges with machine learning?\u201d<\/p>\n","protected":false},"author":133,"featured_media":11220,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"content-type":"","inline_featured_image":false,"footnotes":""},"categories":[3],"tags":[267,265,289],"location":[397],"class_list":["post-11217","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech-focus","tag-machine-learning","tag-mlops","tag-operationalising"],"acf":[],"yoast_head":"\nWhat do practitioners see as the main challenges in Operationalising Machine Learning solutions? | Equal Experts<\/title>\n<meta name=\"description\" content=\"Find out what data scientists answered when asked the question, \u201cWhat do you see as the main challenges with machine learning?\u201d\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/\" \/>\n<meta property=\"og:locale\" content=\"en_GB\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"What do practitioners see as the main challenges in Operationalising Machine Learning solutions?\" \/>\n<meta property=\"og:description\" content=\"Find out what data scientists answered when asked the question, \u201cWhat do you see as the main challenges with machine learning?\u201d\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/\" \/>\n<meta property=\"og:site_name\" content=\"Equal Experts\" \/>\n<meta property=\"article:published_time\" content=\"2022-07-13T08:06:02+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-12-10T02:17:53+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.equalexperts.com\/wp-content\/uploads\/2022\/07\/MLOps-challenges.fb_.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1200\" \/>\n\t<meta property=\"og:image:height\" content=\"631\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Simon Case\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"What do practitioners see as the main challenges in Operationalising Machine Learning solutions?\" \/>\n<meta name=\"twitter:description\" content=\"Find out what data scientists answered when asked the question, \u201cWhat do you see as the main challenges with machine learning?\u201d\" \/>\n<meta name=\"twitter:creator\" content=\"@EqualExperts\" \/>\n<meta name=\"twitter:site\" content=\"@EqualExperts\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"Simon Case\" \/>\n\t<meta name=\"twitter:label2\" content=\"Estimated reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"2 minutes\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/\"},\"author\":{\"name\":\"Simon Case\",\"@id\":\"https:\/\/www.equalexperts.com\/#\/schema\/person\/461daa125fcd274669eb26dfbef20369\"},\"headline\":\"What do practitioners see as the main challenges in Operationalising Machine Learning solutions?\",\"datePublished\":\"2022-07-13T08:06:02+00:00\",\"dateModified\":\"2024-12-10T02:17:53+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/\"},\"wordCount\":284,\"publisher\":{\"@id\":\"https:\/\/www.equalexperts.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/#primaryimage\"},\"thumbnailUrl\":\"https:\/\/www.equalexperts.com\/wp-content\/uploads\/2022\/07\/MLOps-challenges-lead.png\",\"keywords\":[\"machine learning\",\"mlops\",\"operationalising\"],\"articleSection\":[\"Tech Focus\"],\"inLanguage\":\"en-GB\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/\",\"url\":\"https:\/\/www.equalexperts.com\/blog\/tech-focus\/challenges-in-operationalising-mlops\/\",\"name\":\"What do practitioners see as the main challenges in Operationalising Machine Learning solutions? 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