Course: Recommender Systems

$49.00
$59.29 incl. vat

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duration: 3 hours |

Language: English (US) |

access duration: 90 days |

Details

If you work in machine learning, it is extremely helpful to implement recommendation systems (also called recommender systems). These systems can dramatically increase user engagement and goodwill towards your products or brand. You can use this course to comprehend the math behind recommendation systems and how to apply latent factor analysis to make recommendations to users. In this course, you will examine the intuition behind recommender systems before investigating two of the main techniques used to build them: content-based filtering and collaborative filtering. You will also learn to use the rating matrix for the Python programming language.

Result

After completing this course, you'll be able to build a recommendation system model that best suits your products and users.

Prerequisites

You have at least basic knowledge of the Python programming language and machine learning.

Target audience

Software Developer, Web Developer

Content

Recommender Systems

3 hours

Recommender Systems: Under the Hood of Recommendation Systems

  • Users marvel at a system's ability to recommend items they're likely to appreciate. As someone working with machine learning, implementing these recommendation systems (also called recommender systems) can dramatically increase user engagement and goodwill towards your products or brand.
  • Use this course to comprehend the math behind recommendation systems and how to apply latent factor analysis to make recommendations to users.
  • Examine the intuition behind recommender systems before investigating two of the main techniques used to build them: content-based filtering and collaborative filtering.
  • Moving on, explore latent factor analysis by decomposing a ratings matrix into its latent factors using the gradient descent algorithm and implementing this technique to decompose a ratings matrix using the Python programming language.
  • By the end of this course, you'll be able to build a recommendation system model that best suits your products and users.

Course options

We offer several optional training products to enhance your learning experience. If you are planning to use our training course in preperation for an official exam then whe highly recommend using these optional training products to ensure an optimal learning experience. Sometimes there is only a practice exam or/and practice lab available.

Optional practice exam (trial exam)

To supplement this training course you may add a special practice exam. This practice exam comprises a number of trial exams which are very similar to the real exam, both in terms of form and content. This is the ultimate way to test whether you are ready for the exam. 

Optional practice lab

To supplement this training course you may add a special practice lab. You perform the tasks on real hardware and/or software applicable to your Lab. The labs are fully hosted in our cloud. The only thing you need to use our practice labs is a web browser. In the LiveLab environment you will find exercises which you can start immediatelyThe lab enviromentconsist of complete networks containing for example, clients, servers,etc. This is the ultimate way to gain extensive hands-on experience. 

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