Ever wonder how Netflix decides what movies to recommend for you? Or how Amazon recommends books? We can get a feel for how it works by building a simplified recommender of our own!
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Java Programming and Software Engineering Fundamentals
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Über diesen Kurs
Kompetenzen, die Sie erwerben
- Data Structure
- Interfaces
- Software Design
- Java Programming
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Duke University
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Lehrplan - Was Sie in diesem Kurs lernen werden
Introducing the Recommender
You will start out the capstone project by taking a look at the features of a recommender engine. Then you will choose how to read in and organize user, ratings, and movie data in your program. The programming exercise will provide a check on your progress before moving on to the next step.
Simple Recommendations
Your second step in building a recommender will focus on making simple recommendations based on the average ratings that a movie receives. You'll also make sure that each recommended movie has a least a minimal number of user ratings before including it in your recommendations. Throughout this step you are encouraged you use your knowledge of the seven step process to design useful algorithms and successful programs to solve the challenges you will face.
Interfaces, Filters, Database
In your third step, you will be encouraged to use interfaces to rewrite your existing code, making it more flexible and more efficient. You will also add filters to select a desired subset of movies that you want to recommend, such as 'all movies under two hours long' or 'all movies made in 2012'. You'll also make your recommendation engine more efficient as you practice software design principles such as refactoring.
Weighted Averages
In your fourth step, you will complete your recommendation engine by finding users in the database that have similar ratings and weighting their input to provide a more personal recommendation for the users of your program. Once you complete this step, you could request ratings of movies from those you know, run your program, and give them recommendations tailored to their own interests and tastes!
Farewell
Congratulations on completing your recommender programming project! As we conclude this capstone course, our instructors have a few parting words as you embark in future learning and work in computer science!
Bewertungen
- 5 stars78,53Â %
- 4 stars17,71Â %
- 3 stars2,04Â %
- 2 stars0,51Â %
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Top-Bewertungen von JAVA PROGRAMMING: BUILD A RECOMMENDATION SYSTEM
Wonderful course learned a lot by making a recommendation system...but some assignments are bit hard to understand what they want from you but everything else is fine. Everyone must take this course
Really good specialization, introduced me a new perspective on how programming really is used for.
This Caption project will help you to apply and have better understanding of the 5 courses in this specialization.
It’s a great project requiring good application of java. Some steps were hard to follow but understood them after some time. A good project to end a specialisation course. Cheers.
Über den Spezialisierung Java Programming and Software Engineering Fundamentals
Take your first step towards a career in software development with this introduction to Java—one of the most in-demand programming languages and the foundation of the Android operating system. Designed for beginners, this Specialization will teach you core programming concepts and equip you to write programs to solve complex problems. In addition, you will gain the foundational skills a software engineer needs to solve real-world problems, from designing algorithms to testing and debugging your programs.

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