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Individual Challenge - Data Science Basic
Individual Challenge - Data Science Basic
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Test your knowledge on data science concepts and Python programming with this engaging quiz
Flashcards
75 cards
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Questions
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Answers
1
Environment for online Python?
Google Colab
Google Spreadsheet
Google One
Anaconda
2
What is a simple random sample?
Equal chance of selection
Taken in a certain order
Taken from a subgroup
Taken systematically
3
What is Data Science?
A branch of physics
Interdisciplinary field
Study of numbers
A programming language
4
Technique to prevent overfitting?
Initializing weights
Dropout
Using dense layers
Scaling
5
Common challenge in K-Means?
Selecting target variable
Ensuring equidistant points
Avoiding dimensionality curse
Optimal number of clusters
6
Main goal of prompt engineering?
Design inputs for outputs
Improve model performance
Fine-tune language models
Increase dataset size
7
Statistical power concerns?
Type I error
Type II error
Sample size
Skewness
8
What does LLM stand for in AI?
Limited Linguistic Model
Long Latency Model
Learned Language Mapping
Large Language Model
9
Correct statement about if-elif-else?
Declare variables
Sort lists
Create logical branches
Create loops
10
Algorithm for predicting continuous numeric value?
Random Forest Regressor
Naive Bayes Classifier
Decision Tree Classifier
K-Means Clustering
11
Which problem does an LSTM network aim to address in traditional RNNs?
Vanishing gradient problem and long term memory
Classification tasks
Overfitting
Reducing model complexity
12
What does K represent in K-Means?
Number of features
Maximum distance
Number of clusters
Number of data points
13
What does variance measure?
Mode of the data
Median of the data
Frequency of the data
Dispersion from the mean
14
Key difference between supervised and unsupervised?
Clusters vs classifies data
Uses labeled vs unlabeled data
Uses decision trees vs uses neural networks
Supervised learning is more accurate
15
Suitable dataset for emotion recognition?
Translated text documents
Stock price movements
Legal documents
Labeled with emotions
16
Gate deciding information in LSTM?
Output gate
Memory gate
Forget gate
Input gate
17
Access columns in Pandas DataFrame?
Using df['column_name']
Using df.column()
Using df.column_name
Using df[list_of_column_names]
18
What does coef_ attribute represent in code below?
Learned weights for features
Predicted values for training
Importance in decision tree
Accuracy score of model
19
Clustering algorithm not needing clusters specified?
K-Means
Random Forest
Decision Tree
DBSCAN
20
Activation function for binary classification?
Softmax
Tanh
ReLU
Sigmoid
21
When to use stratified sampling?
Data is symmetrically distributed
Data is evenly distributed
Divided into homogeneous subgroups
Outliers in data
22
Example of basic prompt template?
Find grammatical errors
Translate {text} to {language}
Explain content in detail
Visualize text with diagrams
23
True about Random Forest Regressor?
Clustering algorithm
Works with categorical data
Used for binary classification
Creates multiple decision trees
24
Function of a histogram?
Displays frequency of data
Shows relationship between variables
Measures symmetry of data
Calculates the median
25
What is systematic sampling?
Take samples in order
Take random samples
Take samples based on strata
Take samples from small population
26
Create DataFrame in Pandas?
Using pd.Series()
Using pd.Table()
Using pd.DataFrame()
Using pd.DictionaryFrame()
27
Why are few-shot prompts effective?
Focus on numeric data
Increase training dataset size
Demonstrate patterns for model
Reduce memory in model
28
Task of Support Vector Regressor perform?
Dimensionality reduction
Regression
Clustering
Classification
29
A truncated or heart-cut distribution occurs when?
No peaks
More than two peaks
Data is normally distributed
Missing data at tail
30
What does epoch refer to?
Batch of training samples
Complete pass through data
Layer in the network
Single training sample
31
Function of head() in Pandas?
Sorts DataFrame
Removes first row
Displays first row
Adds new row
32
Which of the following describes a neural network with multiple layers between input and output?
Decision Tree
Shallow Neural Network
Deep Neural Network
Linear Model
33
What does Langchain's ConversationBufferMemory store?
Only last user message
Full history of conversation
Configuration files
Pre-trained weights
34
Pay attention to the image below!
Trains a Random Forest classifier with 42 trees on the training data
Trains Random Forest regressor with 100 trees on training data
Evaluates a Random Forest model with 100 trees on the training data
Predicts the target variable with a Random Forest regressor
35
Algorithm for binary or multi-class classification?
Random Forest Regressor
DBSCAN
K-Means
Naive Bayes Classifier
36
What does softmax activation function return?
Binary output
Single value between 0 and 1
Logarithmic output
Probability distribution over classes
37
Example of lemmatization?
Splitting sentence into words
Converting running to run
Removing punctuation
Removing conjunctions
38
Output of len([4, 7, 5, 4])?
2
3
5
4
39
Which is part of Supervised Learning?
Association Rule
Clustering
Regularization
Classification
40
Purpose of hypothesis testing?
Determine spread of data
Measure frequency of values
Test relationship between variables
Determine statistical significance
41
What does LSTM stand for?
Large Sequence Training Model
Least Square Transformation Model
Long Short-Term Memory
Learning Sequential Task Model
42
Output of df.shape in Pandas?
Only number of rows
Number of columns
Tuple of rows and columns
Dataframe in array form
43
Common loss function for regression?
Hinge Loss
Cross-Entropy
Kullback-Leibler Divergence
Mean Squared Error
44
What is a "type I error" in hypothesis testing?
Accepting true null hypothesis
Accepting true alternative
Rejecting false alternative
Rejecting true null hypothesis
45
Cost function for binary classification?
Mean Squared Error
Hinge Loss
Mean Absolute Error
Binary Cross-Entropy
46
Purpose of tool call in LangChain?
Interact with external tools
Perform sentiment analysis
Generate text without context
Visualize data from conversation
47
Clustering algorithm based on density?
K-Means
Random Forest
DBSCAN
Decision Tree
48
How to define a function in Python?
Using lambda keyword
Using def keyword
Using function keyword
Using func keyword
49
Which algorithm is commonly used for regression tasks and constructs a model in the form of a tree structure?
Decision Tree Regressor
Support Vector Classifier
Naive Bayes Classifier
K-Means Clustering
50
Key characteristic of few-shot prompt?
Provides few examples
Used for binary tasks
Contains no examples
Optimized for real-time
51
What is correlation?
Total number of observations
Relationship between two variables
Average of two variables
Measure of data dispersion
52
Best describes classification in ML?
Grouping data points
Categorizing data into labels
Measuring error rate
Predicting continuous output
53
Sentiment analysis aims to determine?
Topic of text
Keywords in text
Polarity of text
Summary of text
54
Purpose of y_pred = model.predict(X_test)?
Initializes new model
Trains model on test data
Predicts target variable
Calculates model accuracy
55
What is the purpose of StandardScaler() in code below?
Scale features to range
Remove outliers
Standardize features
Convert categorical to numerical
56
Positive skewness occurs when?
Mode
Mean > Median > Mode
Mean
Mean = Median = Mode
57
What is an outlier?
Deviates from pattern
Missing from dataset
Within interquartile limits
Close to the mean
58
What is variance?
Frequency of data values
Spread of data from mean
Relationship between variables
Number of observations
59
NOT true about Decision Tree Regressor?
Model in tree structure
Uses Bayes' theorem for predictions
Handles categorical data
Predicting continuous values
60
Hypothesis testing with p-value is used to?
Measure correlation
Test statistical significance
Measure variance
Calculate means
61
What does TF-IDF stand for?
Text Frequency-Inverse Data Frequency
Token Frequency-Individual Document Frequency
Term Frequency-Inverse Document Frequency
Term Frequency-Individual Data Frequency
62
Normal distribution characteristics, except?
Mean = median = mode
Data centered on peak
Values evenly spread
Symmetrical about center
63
Difference between bimodal and multimodal?
Bimodal refers to the distribution of grouped data, multimodal does not
Bimodal is a symmetric distribution, multimodal is not
Bimodal has two peaks, multimodal has more than two peaks
Bimodal has one peak, multimodal has two peaks
64
Which is NOT a type of Machine Learning?
Unsupervised Learning
Semi Supervised Learning
Semi Reinforcement Learning
Supervised Learning
65
Common application of NLP?
Object Detection
Speech Recognition
Web Development
Face Detection
66
Algorithm uses "gini impurity" or "information gain" to build a model?
Naive Bayes Classifier
Support Vector Regressor
Decision Tree Regressor
K-Means Clustering
67
What is range in statistics?
Median of the data
Frequency of occurrence
Difference between highest and lowest
Mean of the data
68
What does NLP stand for?
Natural Learning Process
Natural Language Processing
Networked Language Programming
Neuro-Linguistic Programming
69
Best algorithm for binary classification?
Naive Bayes Classifier
Decision Tree Regressor
Random Forest Regressor
K-Means Clustering
70
Purpose of loss function in deep learning?
Initialize weights
Update model architecture
Measure model performance
Preprocess input data
71
In symmetric distribution, mean, median, mode will?
Be the same
Always greater than mean
Be unrelated
Be very different
72
Display statistical description in Pandas?
Using describe()
Using detail()
Using stats()
Using summary()
73
What are quartiles in statistics?
Divides data into two parts
Average value of data
Deviation from the mean
Divides data into four parts
74
What is the mode?
Extreme values in data
Mean of the data
Middle value of data
Most frequently occurring value
75
Difference between list and tuple?
List cannot be changed after it is defined
Tuple is slower than list
Tuple is mutable, while list is immutable
List is mutable, while tuple is immutables
