WorksheetsMachine Learning for ADSA
Total questions: 69
Worksheet time: 58mins
What is Machine Learning? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
What kind of learning algorithm for "Future stock prices or currency exchange rates"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
Which of the following is not type of learning?
Semi-unsupervised Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
This picture shows an application of ...
Supervised Learning: Classification
Unsupervised Learning: Clustering
Unsupervised Learning: Prediction
Supervised Learning: Regression
Field of study that gives computers the ability to learn without being explicitly programmed.
Deep Learning
Machine Learning
Data Science
What would make a robot intelligent?
It responds to the environment.
It responds to the environment according to previous experiences.
It calculates mathematical problems faster than human minds.
It can jump 1.5 meters higher than humans.
A major benefit of an machine with AI is
it could do a job too dangerous for a human
it could love you like a brother
it could chop up your vegetables
A major benefit of an machine with AI is
it could do a job too dangerous for a human
it could love you like a brother
it could chop up your vegetables
A major benefit of an machine with AI is
it could do a job too dangerous for a human
it could love you like a brother
it could chop up your vegetables
A major benefit of an machine with AI is
it could do a job too dangerous for a human
it could love you like a brother
it could chop up your vegetables
What would make a robot intelligent?
It responds to the environment.
It responds to the environment according to previous experiences.
It calculates mathematical problems faster than human minds.
It can jump 1.5 meters higher than humans.
A major benefit of an machine with AI is
it could do a job too dangerous for a human
it could love you like a brother
it could chop up your vegetables
What is Machine Learning? (Choose 3 Answers)
Artificial Intelligence
Machine Learning
Data Statistics
Deep Learning
What kind of learning algorithm for "Future stock prices or currency exchange rates"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
What kind of learning algorithm for "Facial identities or facial expressions"?
Recognizing Anomalies
Prediction
Generating Patterns
Recognition Patterns
Which of the following is not type of learning?
Semi-unsupervised Learning
Unsupervised Learning
Supervised Learning
Reinforcement Learning
This picture shows an application of ...
Supervised Learning: Classification
Unsupervised Learning: Clustering
Unsupervised Learning: Prediction
Supervised Learning: Regression
Field of study that gives computers the ability to learn without being explicitly programmed.
Deep Learning
Machine Learning
Data Science
What is the primary goal of EDA?
Building machine learning models
Cleaning data for deployment
Understanding the data's characteristics and patterns
Storing data in databases
Which Python library is most commonly used for EDA visualization?
NumPy
Pandas
Matplotlib
TensorFlow
In EDA, the term "outlier" refers to:
A missing value in a dataset
A data point that is significantly different from others
A feature with too many categories
A value with no label
Which function in Pandas is used to get the first few rows of a DataFrame?
head()
first()
top()
sample()
Which plot is best for understanding the distribution of a numerical feature?
Line plot
Histogram
Scatter plot
Bar chart
Missing values can be handled by:
Dropping them
Filling with mean/median/mode
Predicting them with other data
All of the above
Which method can be used to detect correlation between numerical variables?
value_counts()
corr()
info()
describe()
One-hot encoding is mainly used for:
Numerical features
Categorical features
Text data
Image data
Which of the following is an example of a derived feature?
The original age column in dataset
Age group created from age column
Missing value count in a dataset
Original height column
Scaling features is important because:
It reduces missing values
It makes features comparable in magnitude
It changes categorical features to numbers
It removes duplicates
Which scaling technique transforms features so they have mean 0 and standard deviation 1?
Min-Max Scaling
Standardization
Normalization
Log transformation
When should you use log transformation in feature engineering?
When data has negative values
When data is normally distributed
When data is highly skewed
When features are already scaled
In feature selection, removing multicollinearity is important because:
It reduces the size of the dataset
It improves model interpretability
It increases missing values
It changes categorical variables to numerical
Which of the following is NOT a feature engineering technique?
Binning
Polynomial features
Gradient boosting
Feature scaling
If two features have a correlation of 0.98, what might you consider?
Drop one of them
Keep both as they are
Scale them
Convert to categorical
Suppose you have a dataset where feature A is in meters and feature B is in kilometers. What is the first step to make them comparable for model training?
Drop one feature
Scale both features to the same range
Encode the features
Fill missing values
After encoding categorical variables using one-hot encoding, the dataset size increases drastically. Which technique can reduce dimensionality while retaining most information?
Standardization
PCA (Principal Component Analysis)
Min-Max scaling
Log transformation
A feature has many zero values with a few large positive numbers. Which transformation can help make this feature more normally distributed?
Square root transformation
Min-Max scaling
Standardization
Polynomial features
During EDA, you notice that the target variable is imbalanced (90% class A, 10% class B). Which approach is NOT a valid solution?
Oversampling minority class
Undersampling majority class
Adding noise to features
Using SMOTE
You create a new feature by multiplying two existing features. This is an example of:
Feature scaling
Feature interaction
Dimensionality reduction
Feature selection
apakah arti (NaN) di dalam sebuah dataset?
Missing data
Unknown value
Outlier
Placeholder
Metode apa yang digunakan untuk mendeteksi adanya nilai null dalam sebuah DataFrame?
find_nulls()
isnan()
isnull()
null_check()
untuk apa metode fillna()?
Mengganti nilai null dengan median
Mengganti nilai null dengan mean
Mengganti nilai null dengan sebuah nilai
Membuat kategori baru dari null
Apa saja yang merupakan bagian dari proses feature engineering?
Membuat feature baru dari data yang sudah ada
Melakukan evaluasi hasil
Melakukan Visualisasi Data
Menghapus outliers dari dataset
proses transformasi data menjadi fitur-fitur yang lebih representatif dalam membantu menyelesaikan masalah dengan lebih baik disebut
Creation Enginering
Model transformation
Feature engineering
Creation transformation
Jenis-jenis scaling antara lain:
StandardScaler
MinMaxScaler
RobustScaler
OpenScaler
Jika sebuah kolom memiliki 6 nilai unik, berapa kolom yang terbentuk jika menggunakan OneHotEncoder?
6
1
2
3
Proses Encoding dilakukan untuk?
Mengubah data kategorik menjadi numerik
Mengubah data numerik menjadi kategorik
Mengubah data Ordinal menjadi Nominal
Mengubah data Nominal menjadi Ordinal
Untuk melakukan encoding pada data target atau y dapat menggunakan
LabelEncoder
OneHotEncoder
OrdinalEncoder
TargetEncoder
Mengapa Data perlu di scaling terlebih dahulu sebelum masuk pemodelan?
Agar data menjadi 1
Agar data berada dalam skala yang sama
Agar data lebih teratur
agar data menjadi minus
What is Matplotlib?
A cooking recipe book
A type of flower
A new programming language
A plotting library for Python
Name three types of plots that can be created using Matplotlib.
Box plot
1. Line plot 2. Scatter plot 3. Bar plot
Pie plot
Histogram
Explain the difference between plt.plot() and plt.scatter() in Matplotlib.
plt.plot() is used to create bar plots, while plt.scatter() is used to create line plots.
plt.plot() is used to create scatter plots, while plt.scatter() is used to create line plots.
plt.plot() is used to create pie charts, while plt.scatter() is used to create scatter plots.
plt.plot() is used to create line plots, while plt.scatter() is used to create scatter plots.
How can you change the color of a plot in Matplotlib?
By using the 'size' parameter in the plot function.
By using the 'label' parameter in the plot function.
By using the 'marker' parameter in the plot function.
By using the 'color' parameter in the plot function.
What is the purpose of adding labels to the x-axis and y-axis in a Matplotlib plot?
To hide the data
To make the plot look more colorful
To confuse the audience
To provide context and understanding of the data being presented in the plot.
Explain the use of plt.subplot() in Matplotlib.
It is used to create 3D plots in Matplotlib.
It is used to change the color scheme of the entire figure in Matplotlib.
It is used to create a grid of subplots within a single figure.
It is used to add a title to the entire figure in Matplotlib.
What is the function of plt.legend() in Matplotlib?
Add a legend to the current axes.
Change the color of the plot
Create a new figure
Remove the axes from the plot
How can you save a Matplotlib plot as an image file?
Using the 'display' method
Using the 'savefig' method
Using the 'export' method
Using the 'print' method
Explain the concept of subplots in Matplotlib.
Subplots in Matplotlib can only be used for line plots
Subplots in Matplotlib are used to create 3D plots
Subplots in Matplotlib are not supported in Jupyter notebooks
Subplots in Matplotlib allow us to create multiple plots within the same figure.
What is the role of plt.title() in Matplotlib?
To add a legend to the plot
To change the color of the plot
To adjust the size of the plot
To set the title of the plot.
Which function is used to create a pie chart in Matplotlib?
plt.pie()
plt.piechart()
plt.chart()
plt.pieplot()
How can you explode a slice in a pie chart to emphasize it?
Use the explode parameter in plt.pie()
Use the highlight parameter in plt.pie()
Use the slice parameter in plt.pie()
Use the accent parameter in plt.pie()
What does the plt.scatter() function do?
Creates a line plot
Creates a scatter plot
Creates a histogram
Creates a pie chart
Which function in Matplotlib can be used to customize the size of points in a scatter plot?
plt.scatter()
plt.plot()
plt.bar()
plt.hist()
How can you add a legend to a scatter plot?
plt.legend()
plt.add_legend()
plt.show_legend()
plt.insert_legend()
Which function is used to create a violin plot in Matplotlib?
plt.violin()
plt.boxplot()
plt.violinplot()
plt.plot()
What does the c parameter in plt.scatter() control?
Which parameter in plt.pie() defines how much each slice is exploded from the center?
explode
offset
separation
dist
