{"id":6828,"date":"2022-04-28T20:48:11","date_gmt":"2022-04-28T20:48:11","guid":{"rendered":"https:\/\/www.tun.com\/courses\/2019\/12\/23\/ai-workflow-machine-learning-visual-recognition-and-nlp\/"},"modified":"2022-04-28T20:48:11","modified_gmt":"2022-04-28T20:48:11","slug":"ai-workflow-machine-learning-visual-recognition-and-nlp","status":"publish","type":"post","link":"https:\/\/www.tun.com\/courses\/ai-workflow-machine-learning-visual-recognition-and-nlp\/ibm\/","title":{"rendered":"AI Workflow: Machine Learning, Visual Recognition and NLP"},"content":{"rendered":"
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Description<\/h2>\n

This is the fourth course in the IBM AI Enterprise Workflow Certification specialization.\u00a0\u00a0\u00a0 You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.\u00a0<\/p>\n

Course 4 covers the next stage of the workflow, setting up models and their associated data pipelines for a hypothetical streaming media company.\u00a0 The first topic covers the complex topic of evaluation metrics, where you will learn best practices for a number of different metrics including regression metrics, classification metrics, and multi-class metrics, which you will use to select the best model for your business challenge.\u00a0 The next topics cover best practices for different types of models including linear models, tree-based models, and neural networks.\u00a0 Out-of-the-box Watson models for natural language understanding and visual recognition will be used.\u00a0 There will be case studies focusing on natural language processing and on image analysis to provide realistic context for the model pipelines.
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\nBy the end of this course you will be able to:
\nDiscuss common regression, classification, and multilabel classification metrics
\nExplain the use of linear and logistic regression in supervised learning applications
\nDescribe common strategies for grid searching and cross-validation
\nEmploy evaluation metrics to select models for production use
\nExplain the use of tree-based algorithms in supervised learning applications
\nExplain the use of Neural Networks in supervised learning applications
\nDiscuss the major variants of neural networks and recent advances
\nCreate a neural net model in Tensorflow
\nCreate and test an instance of Watson Visual Recognition
\nCreate and test an instance of Watson NLU<\/p>\n

Who should take this course?
\nThis course targets existing data science practitioners that have expertise building machine learning models, who want to deepen their skills on building and deploying AI in large enterprises. If you are an aspiring Data Scientist, this course is NOT for you as you need real world expertise to benefit from the content of these courses.
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\nWhat skills should you have?
\nIt is assumed that you have completed Courses 1 through 3 of the IBM AI Enterprise Workflow specialization and you have a solid understanding of the following topics prior to starting this course: Fundamental understanding of Linear Algebra; Understand sampling, probability theory, and probability distributions; Knowledge of descriptive and inferential statistical concepts; General understanding of machine learning techniques and best practices; Practiced understanding of Python and the packages commonly used in data science: NumPy, Pandas, matplotlib, scikit-learn; Familiarity with IBM Watson Studio; Familiarity with the design thinking process.<\/p>\n

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Price: Enroll For Free!<\/h2>\n
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View Class<\/a><\/div>\n
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Language:<\/strong> <\/em>English<\/p>\n<\/div>\n

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Subtitles<\/strong>: <\/em>English<\/p>\n<\/div>\n<\/div>\n

AI Workflow: Machine Learning, Visual Recognition and NLP – IBM<\/strong><\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Description This is the fourth course in the IBM AI Enterprise Workflow Certification specialization.\u00a0\u00a0\u00a0 You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.\u00a0 Course 4 covers the next stage of the workflow, setting up […]<\/p>\n","protected":false},"author":1,"featured_media":19489,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_uag_custom_page_level_css":"","_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[41],"tags":[],"class_list":["post-6828","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ibm"],"aioseo_notices":[],"uagb_featured_image_src":{"full":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"thumbnail":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education-150x150.png",150,150,true],"medium":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education-300x180.png",300,180,true],"medium_large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"large":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"1536x1536":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false],"2048x2048":["https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png",375,225,false]},"uagb_author_info":{"display_name":"Axiom Pegasus","author_link":"https:\/\/www.tun.com\/courses\/author\/magic\/"},"uagb_comment_info":0,"uagb_excerpt":"Description This is the fourth course in the IBM AI Enterprise Workflow Certification specialization.\u00a0\u00a0\u00a0 You are STRONGLY encouraged to complete these courses in order as they are not individual independent courses, but part of a workflow where each course builds on the previous ones.\u00a0 Course 4 covers the next stage of the workflow, setting up…","featured_media_src_url":"https:\/\/www.tun.com\/courses\/wp-content\/uploads\/2019\/12\/IBMonline-education.png","_links":{"self":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/6828","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/comments?post=6828"}],"version-history":[{"count":0,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/posts\/6828\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media\/19489"}],"wp:attachment":[{"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/media?parent=6828"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/categories?post=6828"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.tun.com\/courses\/wp-json\/wp\/v2\/tags?post=6828"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}