Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Fi

Recommender Systems Complete Course Beginner to Advanced - Project 2: Movie Recommendation System Using Collaborative Fi

Assessment

Interactive Video

Information Technology (IT), Architecture, Social Studies

University

Hard

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The video tutorial covers the process of importing essential libraries and datasets for a project. It begins with importing libraries such as operating system, time, numpy, pandas, scipy, sklearn, fuzzy, and matplotlib. The tutorial then moves on to importing datasets, specifically movies and ratings, and reading them into pandas dataframes. The focus is on setting up the environment for data analysis, including specifying data types and columns to be used.

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7 questions

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1.

OPEN ENDED QUESTION

3 mins • 1 pt

What libraries are mentioned for import in the project?

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2.

OPEN ENDED QUESTION

3 mins • 1 pt

Explain the purpose of importing the 'pandas' library in this project.

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3.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the two data sets that are imported in the project?

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4.

OPEN ENDED QUESTION

3 mins • 1 pt

Describe how the 'movies' data frame is created from the CSV file.

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5.

OPEN ENDED QUESTION

3 mins • 1 pt

What data types are assigned to 'movie ID' and 'title' in the data frame?

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6.

OPEN ENDED QUESTION

3 mins • 1 pt

What are the three attributes used for the 'ratings' data set?

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7.

OPEN ENDED QUESTION

3 mins • 1 pt

What is the final step mentioned after importing the libraries and data sets?

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