4.40 (12 reviews)
☑ Identify anomaly within several similar objects
☑ Apply Unsupervised Machine Learning algorithm kmeans
☑ Develop and deploy ShinyApp
☑ Apply Version Control to your projects or activities
☑ Re-use provided template and course exercises in R and ShinyApp
☑ Use Deep Learning Autoencoder Models to Detect Anomalies in Time-Series data
☑ Create a System that Supervises Industrial Process and helps Process Operators to detect anomalies
Inspired by Albert Einstein [1879-1955]
Learn how to identify anomaly within several similar objects with Artificial Intelligence
Working with time-series sensor generated data
Understand how Unsupervised Machine Learning Algorithm works using real life dataset
Learn developing in R and ShinyApp with a possibility to better explore the data, instantly deploy your project
Explained use of Version Control to be organized and save time
Practice 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 practice
Basic understanding on Time-Series data manipulation in R
More approaches of Anomaly Detection including Deep Learning on h2o framework is covered in the course
Practical Developing the idea of Industrial Process Control with Artificial Intelligence with DEMO Shiny Application included
Course video captions are translated to [Chinese-Simplified, Hindi, German, French, Italian, Portuguese, Turkish, Spanish, Malay, Indonesian, Russian] languages
Problem-solving in Manufacturing is 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 Intelligence to 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 will process it through the Unsupervised Machine Learning Algorithm k-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-variables process 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 the Course is the possibility to learn using ShinyApp. This tool 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!
You will learn R by practicing re-using provided material. More over you can easily retain and reuse the knowledge 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.
Join this course to know how to take advantage and use Artificial Intelligence in Problem Solving
Goal of the Course
Introduction to the course
What we will use to learn
Introducing our case study
How to get the most of this course
A bit of theory
Ideas from Problem Solving
What is k-means?
A bit of practice
Install R & R-Studio
Practice Creating your Project and ShinyApp
Get the code easy! A quick win!
Let's Make it Happen or How our ShinyApp work?!
Introduction to the chapter...
User Interface of ShinyApp - build HTML with R functions
Server Part - Calling Data to ShinyApp
Server Part - Manipulating Data in ShinyApp
Using Interactive Inputs
Unsupervised Machine Learning
Creating Dynamic Outputs
Creating user preferred layout
Your Project - New Data Set
Your Project - Introducing New Dataset
Your Project - apply method on other data!!!
Your Project - Solution, use and new challenge!!!
Other Options, including Deep Learning
Deep Learning Autoencoders in H20 - Install & Example
Deep Learning with H2O - Build Model on our data
Deep Learning with H2O - Use Model to predict
Deep Learning with H2O - Put into production with ShinyApp
Detect Anomaly in Industrial Process with Deep Learning
Introducing the task and business need
Selecting the Dataset
Fitting and testing the Model
Demo App in Action!
What have you learnt?
Bonus Lecture Where to go from here?
Congratulation Vladimir, This course is excellent to learn to develop shiny app, I'm now good to try to develop my own apps. It is based on practice which is the best way to learn efficiently. Adding to that you are very active answering every questions in detail giving me the feeling I'm not alone and I have a teacher on my side! I highly recommend this course for those who want learn how to develop shiny application.
The title of the course is not justified. This is not artificial Intelligence course at all. This is just a course, who want to learn R and Shiny.
The instructor is really professional and has given many good examples, I already work as engineer and could use that learning on my daily activities. All the content is good explained, visually efficient, I strongly recommend this course to my work colleagues and hope to enjoy new courses in the future. Thanks for sharing your knowledge with us Vladimir Zhbanko, you are so professional.
Initially, your volume level was adequate. Once into lectures your volume level dropped way down and is now hard to hear even though I have the course volume and my machine/pc volume on high! This is going to be a problem :( Also your grammar/symtax is definitely NOT American. You uise 'you' way to often and inapropriately :( I shall still try to complete the course.