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Java 程序设计:DIY 版本的 Netflix 和亚马逊推荐系统引擎

总览授课大纲常见问题解答制作方价格评分和审阅

主页计算机科学软件开发

Java 程序设计:DIY 版本的 Netflix 和亚马逊推荐系统引擎

Duke University

关于此课程: 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! In this capstone, you will show off your problem solving and Java programming skills by creating recommender systems. You will work with data for movies, including ratings, but the principles involved can easily be adapted to books, restaurants, and more. You will write a program to answer questions about the data, including which items should be recommended to a user based on their ratings of several movies. Given input files on users ratings and movie titles, you will be able to: 1. Read in and parse data into lists and maps; 2. Calculate average ratings; 3. Calculate how similar a given rater is to another user based on ratings; and 4. Recommend movies to a given user based on ratings. 5. Display recommended movies for a given user on a webpage.

此课程适用人群: This course is for anyone who has passed the first four courses in the Java Programming and Software Engineering Fundamentals Specialization, who has the ability to program in Java and design algorithms. Bring together everything you’ve learned to make a movie recommendation system that you can put on the web and send to your colleagues and friends!


制作方:  Duke University
Duke University

  • Robert Duvall

    教学方:  Robert Duvall, Lecturer

    Computer Science

  • Owen Astrachan

    教学方:  Owen Astrachan, Professor of the Practice

    Computer Science

  • Andrew D. Hilton

    教学方:  Andrew D. Hilton, Assistant Professor of the Practice

    Electrical and Computer Engineering

  • Susan H. Rodger

    教学方:  Susan H. Rodger, Professor of the Practice

    Computer Science
基本信息
课程 5(共 5 门,Java Programming and Software Engineering Fundamentals Specialization )
级别Intermediate
承诺学习时间4 weeks of study, 3-6 hours/week
语言
English
如何通过通过所有计分作业以完成课程。
用户评分
4.7 星
平均用户评分 4.7查看学生的留言
授课大纲
第 1 周
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.
2 视频, 3 阅读材料
  1. Reading: Module Description / Resources
  2. 视频: Introduction and Motivation
  3. 视频: Reading and Storing Data
  4. Reading: Programming Exercise: Step One
  5. Reading: End of Module Survey
已评分: Step One
第 2 周
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.
1 视频, 3 阅读材料
  1. Reading: Module Description
  2. 视频: Average Ratings
  3. Reading: Programming Exercise: Step Two
  4. Reading: End of Module Survey
已评分: Step Two
第 3 周
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.
1 视频, 3 阅读材料
  1. Reading: Module Description
  2. 视频: Filtering Recomendations
  3. Reading: Programming Exercise: Step Three
  4. Reading: End of Module Survey
已评分: Step Three
第 4 周
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!
1 视频, 3 阅读材料
  1. Reading: Module Description
  2. 视频: Calculating Weighted Averages
  3. Reading: Programming Exercise: Step Four
  4. Reading: End of Module Survey
已评分: Step Four
已评分: Step Five
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!
1 视频
  1. 视频: Farewell from the Instructor Team

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制作方
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.
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评分和审阅
已评分 4.7,总共 5 个 212 评分
Diar Selimi

good course and very interesting things to learn.

蒋

Thanks to all the teachers!!

MO

Enjoyed it!

YZ

Fantastic course! The instructors were very engaging, the lessons were varied and provided me with a wide variety of information in the field. After completely this course, I definitely feel much more confident working in this field.



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