msb-public
/
ML-For-Beginners
mirror of https://github.com/microsoft/ML-For-Beginners.git
1
0
Code Issues Projects Releases Wiki Activity

moar quizzes

Browse Source
pull/34/head
Jen Looper 4 years ago
parent cc714200b3
commit 35a6dbc021
2 changed files with 44 additions and 36 deletions
Show Stats Download Patch File Download Diff File

2
README.md
Unescape View File

@ -18,7 +18,7 @@ Travel with us around the world as we apply these classic techniques to data fro
**Hearty thanks to our authors (list all authors here)**
**🙏Special thanks🙏 to our Microsoft Student Ambassador Reviewers**, notably Rishit Dagli, Rohan Raj, Muhammad Sakid Khan Inan, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, and Snigdha Agarwal
**🙏Special thanks🙏 to our Microsoft Student Ambassador reviewers and content contributors**, notably Rishit Dagli, Rohan Raj, Muhammad Sakid Khan Inan, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, and Snigdha Agarwal
**Teachers**, we have [included some suggestions](for-teachers.md) on how to use this curriculum. If you would like to create your own lessons, we have also included a [lesson template](lesson-template/README.md)

78
quiz-app/src/assets/translations/en.json
Unescape View File

@ -6,7 +6,7 @@
"quizzes": [
{
"id": 1,
"title": "Lesson 1 - Intro to ML: Pre-Lecture Quiz",
"title": "Introduction to Machine Learning: Pre-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
@ -59,7 +59,7 @@
},
{
"id": 2,
"title": "Lesson 1 - Intro to ML: Post-Lecture Quiz",
"title": "Introduction to Machine Learning: Post-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
@ -112,7 +112,7 @@
},
{
"id": 3,
"title": "Lesson 1 - Intro to ML: Post-Lecture Quiz",
"title": "History of Machine Learning: Post-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
@ -165,7 +165,7 @@
},
{
"id": 4,
"title": "Lesson 1 - Intro to ML: Post-Lecture Quiz",
"title": "History of Machine Learning: Post-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
@ -218,7 +218,7 @@
},
{
"id": 5,
"title": "Lesson 1 - Intro to ML: Post-Lecture Quiz",
"title": "Ethics of Machine Learning: Post-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
@ -271,7 +271,7 @@
},
{
"id": 6,
"title": "Lesson 1 - Intro to ML: Post-Lecture Quiz",
"title": "Ethics of Machine Learning: Post-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
@ -438,51 +438,55 @@
},
{
"id": 9,
"title": "Lesson 1 - Intro to ML: Pre-Lecture Quiz",
"title": "Build a Regression Model using Scikit-Learn: Prepare and Visualize Data: Pre-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
"questionText": "Which of these Python modules is used to plot the visualization of data?",
"answerOptions": [
{
"answerText": "a",
"answerText": "Numpy",
"isCorrect": "false"
},
{
"answerText": "b",
"isCorrect": "true"
"answerText": "Scikit-Learn",
"isCorrect": "false"
},
{
"answerText": "c",
"isCorrect": "false"
"answerText": "Matplotlib",
"isCorrect": "true"
}
]
},
{
"questionText": "q2",
"questionText": "If you want to understand the spread or the other characteristics of data points of your dataset, then perform:",
"answerOptions": [
{
"answerText": "a",
"answerText": "Data Visualization",
"isCorrect": "true"
},
{
"answerText": "b",
"answerText": "Data Preprocessing",
"isCorrect": "false"
},
{
"answerText": "Train Test Split",
"isCorrect": "false"
}
]
},
{
"questionText": "q3",
"questionText": "Which of these is a part Data Visualization step in a Machine Learning project?",
"answerOptions": [
{
"answerText": "a",
"answerText": "Incorporating a certain Machine Learning algorithm",
"isCorrect": "false"
},
{
"answerText": "b",
"answerText": "Creating a pictorial representation of data using different plotting methods",
"isCorrect": "true"
},
{
"answerText": "c",
"answerText": "Normalizing the values of a dataset",
"isCorrect": "false"
}
]
@ -491,51 +495,55 @@
},
{
"id": 10,
"title": "Lesson 1 - Intro to ML: Post-Lecture Quiz",
"title": "Build a Regression Model using Scikit-Learn: Prepare and Visualize Data: Post-Lecture Quiz",
"quiz": [
{
"questionText": "q1",
"questionText": "Which of these code snippets is correct based on this lesson, if you want to check for the presence of missing values in your dataset? Suppose the dataset is stored in a variable named 'dataset' which is a Pandas DataFrame object.",
"answerOptions": [
{
"answerText": "a",
"isCorrect": "false"
"answerText": "dataset.isnull().sum()",
"isCorrect": "true"
},
{
"answerText": "b",
"isCorrect": "true"
"answerText": "findMissing(dataset)",
"isCorrect": "false"
},
{
"answerText": "c",
"answerText": "sum(null(dataset))",
"isCorrect": "false"
}
]
},
{
"questionText": "q2",
"questionText": "Which of these plotting methods is useful when you would like to understand the spread of different groups of datapoints from your dataset?",
"answerOptions": [
{
"answerText": "a",
"isCorrect": "true"
"answerText": "Scatter Plot",
"isCorrect": "false"
},
{
"answerText": "b",
"answerText": "Line Plot",
"isCorrect": "false"
},
{
"answerText": "Bar Plot",
"isCorrect": "true"
}
]
},
{
"questionText": "q3",
"questionText": "What can Data Visualization NOT tell you?",
"answerOptions": [
{
"answerText": "a",
"answerText": "Relationships among datapoints",
"isCorrect": "false"
},
{
"answerText": "b",
"answerText": "The source from where the dataset is collected",
"isCorrect": "true"
},
{
"answerText": "c",
"answerText": "Finding the presence of outliers in the dataset",
"isCorrect": "false"
}
]

Write Preview
Loading…
Cancel
Save