Identify Problems with Artificial Intelligence – Case Study | Data Science Online Course by Udemy

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Industry 4.0: Bring your Complex Problem Solving Skills to a new level. Contains Deep Learning Tutorial.

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Identify Problems with Artificial Intelligence – Case Study

Inspired by Albert Einstein [1879-1955]Course summary: Learn how to identify anomaly within several similar objects with Artificial IntelligenceWorking withtime-seriessensor generateddataUnderstand how Unsupervised Machine Learning Algorithmworks using real life datasetLearn developing in R and ShinyApp with a possibility to better explore the data, instantly deploy your projectExplained use of Version Control to be organized and save timePractice with real life generalized Dataset coming from Manufacturing! Versatile method is presented using a Case Study approach. This method helped to discover real life inefficiency and to solve the problem! Start with R here! Step by step introduction with examples and practiceBasic understanding on Time-Series data manipulation in RMore approaches of Anomaly Detection including Deep Learningon h2o frameworkiscovered in the coursePractical Developing the idea of IndustrialProcess Control with Artificial Intelligence with DEMO ShinyApplication includedCourse video captions are translated to[Chinese-Simplified, Hindi, German, French, Italian, Portuguese, Turkish, Spanish, Malay, Indonesian, Russian] languagesDescribed: Problem-solvingin Manufacturingis usually perceived as a slow and boring activity especially when many possible factors involved. At the same time it’s often common that problems going on and on unobserved which is very costly. Is it possible to apply Artificial Intelligenceto help human to identify the problem? Is it possible to dedicate this boring problem solving activity to computer? Apparently yes! This course will help you to combine popular problem-solving technique called “is/is not” with Artificial Intelligence in order to quickly identify the problem. We will use data coming from four similar Machines. We willprocess it through the Unsupervised Machine Learning Algorithmk-means. Once you get intuition understanding how this system work You will be amazed to see how easy and versatile the concept is. In our project you will see that helped by Artificial Intelligence Human eye will easily spot the problem. Course will also exploit different other methods of Anomaly Detection. Probably the most interesting one is to use Deep Learning Autoencoders models built with help of H2O Platform in R.Using collected data and Expert Knowledge for Process Control with AI: In this course we will build and demo-try entire multi-variablesprocess supervision system. Process Expert should select dataset coming from the ideally working process. Deep Learning model will be fit to that specific pattern. This model can be used to monitor the process as the new data is coming in. Anomaly in the process then can be easily detected by the process operators. Ready for Production: Another great value from theCourse isthe possibility to learn usingShinyApp. Thistool will help you to instantly deploy your data project in no time! In fact all examples we will study will be ready to be deployed in real scenario! Additionally: You will learn R by practicing re-using provided material. More over you can easilyretain and reusetheknowledge from the course-all lectures with code are available as downloadable html files. You will get useful knowledge on Version Control to be super organized and productive. Finally: Join this course to know how to take advantage and use Artificial Intelligence in Problem Solving

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