Podcast
Questions and Answers
Which programming language is taught in the book 'Data Science from Scratch'?
Which programming language is taught in the book 'Data Science from Scratch'?
- C++
- R
- Java
- Python (correct)
What are the core subjects covered in the book 'Data Science from Scratch'?
What are the core subjects covered in the book 'Data Science from Scratch'?
- Linear Algebra, Statistics, and Probability (correct)
- Biology, Chemistry, and Physics
- Grammar, Vocabulary, and Syntax
- Calculus, Algebra, and Geometry
Which of the following is NOT a model implemented in 'Data Science from Scratch'?
Which of the following is NOT a model implemented in 'Data Science from Scratch'?
- Linear regression
- Random forest (correct)
- Naive Bayes
- k-nearest neighbors
What are some of the topics explored in 'Data Science from Scratch'?
What are some of the topics explored in 'Data Science from Scratch'?
What is the goal of 'Data Science from Scratch'?
What is the goal of 'Data Science from Scratch'?
True or false: 'Data Science from Scratch' is a book that helps you learn the math and statistics at the core of data science?
True or false: 'Data Science from Scratch' is a book that helps you learn the math and statistics at the core of data science?
True or false: The book covers the basics of linear algebra, statistics, and probability?
True or false: The book covers the basics of linear algebra, statistics, and probability?
True or false: 'Data Science from Scratch' teaches you how to collect, explore, clean, munge, and manipulate data?
True or false: 'Data Science from Scratch' teaches you how to collect, explore, clean, munge, and manipulate data?
True or false: The book dives into the fundamentals of machine learning?
True or false: The book dives into the fundamentals of machine learning?
True or false: 'Data Science from Scratch' covers topics such as recommender systems, natural language processing, network analysis, MapReduce, and databases?
True or false: 'Data Science from Scratch' covers topics such as recommender systems, natural language processing, network analysis, MapReduce, and databases?
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