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NUMPY FOR DS.pdf
4.5 MB
Let's start at the top...
NumPy contains a broad array of functionality for fast numerical & mathematical operations in Python
The core data-structure within #NumPy is an ndArray (or n-dimensional array)
Behind the scenes - much of the NumPy functionality is written in the programming language C
NumPy functionality is used in other popular #Python packages including #Pandas, #Matplotlib, & #scikitlearn!
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NumPy contains a broad array of functionality for fast numerical & mathematical operations in Python
The core data-structure within #NumPy is an ndArray (or n-dimensional array)
Behind the scenes - much of the NumPy functionality is written in the programming language C
NumPy functionality is used in other popular #Python packages including #Pandas, #Matplotlib, & #scikitlearn!
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This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
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What is the result of the following Python line?
A) True
B) False
C) []
D) None
#Python #Beginner #CodingQuiz #BooleanLogic #LearnPython
print(bool([]))
A) True
B) False
C) []
D) None
#Python #Beginner #CodingQuiz #BooleanLogic #LearnPython
Question 1 (Beginner):
What is the output of the following Python code?
A) 15
B) 555
C) 5 5 5
D) Error
#Python #Beginner #StringOperations #CodingQuiz #LearnPython
What is the output of the following Python code?
print("5" * 3)
A) 15
B) 555
C) 5 5 5
D) Error
#Python #Beginner #StringOperations #CodingQuiz #LearnPython
Question 2 (Intermediate):
What is a common use case for the PCA (Principal Component Analysis) algorithm in machine learning?
A) Hyperparameter tuning
B) Data visualization and dimensionality reduction
C) Gradient descent optimization
D) Model ensembling
#MachineLearning #PCA #DimensionalityReduction #MLQuiz #DataScience
What is a common use case for the PCA (Principal Component Analysis) algorithm in machine learning?
A) Hyperparameter tuning
B) Data visualization and dimensionality reduction
C) Gradient descent optimization
D) Model ensembling
#MachineLearning #PCA #DimensionalityReduction #MLQuiz #DataScience
Question 3 (Advanced):
In reinforcement learning, what does the term “policy” refer to?
A) The sequence of rewards the agent receives
B) The model’s loss function
C) The strategy used by the agent to decide actions
D) The environment's set of rules
#ReinforcementLearning #AI #DeepRL #PolicyLearning #ML
In reinforcement learning, what does the term “policy” refer to?
A) The sequence of rewards the agent receives
B) The model’s loss function
C) The strategy used by the agent to decide actions
D) The environment's set of rules
#ReinforcementLearning #AI #DeepRL #PolicyLearning #ML
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Question 4 (Beginner):
Which of the following is not a valid Python data type?
A) tuple
B) map
C) set
D) float
#Python #DataTypes #Beginner #ProgrammingQuiz #LearnPython
Which of the following is not a valid Python data type?
A) tuple
B) map
C) set
D) float
#Python #DataTypes #Beginner #ProgrammingQuiz #LearnPython
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Question 5 (Intermediate):
In a neural network, what does the ReLU activation function return?
A) 1 / (1 + e^-x)
B) max(0, x)
C) x^2
D) e^x / (e^x + 1)
#NeuralNetworks #DeepLearning #ActivationFunctions #ReLU #AI
In a neural network, what does the ReLU activation function return?
A) 1 / (1 + e^-x)
B) max(0, x)
C) x^2
D) e^x / (e^x + 1)
#NeuralNetworks #DeepLearning #ActivationFunctions #ReLU #AI
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Question 6 (Advanced):
Which of the following attention mechanisms is used in transformers?
A) Hard Attention
B) Additive Attention
C) Self-Attention
D) Bahdanau Attention
#Transformers #NLP #DeepLearning #AttentionMechanism #AI
Which of the following attention mechanisms is used in transformers?
A) Hard Attention
B) Additive Attention
C) Self-Attention
D) Bahdanau Attention
#Transformers #NLP #DeepLearning #AttentionMechanism #AI
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Question 1 (Intermediate):
In Python, which of these is the correct way to create a virtual environment?
A)
B)
C)
D)
#Python #Development #VirtualEnv #Coding
In Python, which of these is the correct way to create a virtual environment?
A)
python create venv
B)
python -m venv myenv
C)
pip install virtualenv
D)
conda make env
#Python #Development #VirtualEnv #Coding
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Question 2 (Advanced):
In machine learning with Python, what does the
A) Controls the shuffling applied to the data before splitting
B) Sets the percentage of data to use for testing
C) Determines the number of CPU cores to use
D) Specifies the type of ML algorithm to apply
#Python #MachineLearning #ScikitLearn #DataScience
In machine learning with Python, what does the
random_state
parameter do in scikit-learn's train_test_split()
function?A) Controls the shuffling applied to the data before splitting
B) Sets the percentage of data to use for testing
C) Determines the number of CPU cores to use
D) Specifies the type of ML algorithm to apply
#Python #MachineLearning #ScikitLearn #DataScience
Question 3 (Expert):
In Python's asyncio, what is the purpose of the
A) To collect garbage from memory
B) To run multiple awaitables concurrently and wait for all to finish
C) To gather system resources for a task
D) To aggregate results from multiple threads
#Python #AsyncIO #Concurrency #AdvancedProgramming
In Python's asyncio, what is the purpose of the
gather()
function?A) To collect garbage from memory
B) To run multiple awaitables concurrently and wait for all to finish
C) To gather system resources for a task
D) To aggregate results from multiple threads
#Python #AsyncIO #Concurrency #AdvancedProgramming
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Question 4 (Intermediate):
When working with Pandas in Python, what does the
A) Creates a copy of the DataFrame before applying changes
B) Modifies the original DataFrame directly
C) Saves the results to a CSV file automatically
D) Enables parallel processing for faster execution
#Python #Pandas #DataAnalysis #DataManipulation
When working with Pandas in Python, what does the
inplace=True
parameter do in DataFrame operations?A) Creates a copy of the DataFrame before applying changes
B) Modifies the original DataFrame directly
C) Saves the results to a CSV file automatically
D) Enables parallel processing for faster execution
#Python #Pandas #DataAnalysis #DataManipulation
Question 5 (Beginner):
What is the correct way to check if a key exists in a Python dictionary?
A)
B)
C)
D)
#Python #Programming #DataStructures #Beginner
What is the correct way to check if a key exists in a Python dictionary?
A)
if key in dict.keys()
B)
if dict.has_key(key)
C)
if key.exists(dict)
D)
if key in dict
#Python #Programming #DataStructures #Beginner
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The correct answers will be published in the comments tomorrow
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Question 6 (Advanced):
In Python's context managers, what is the purpose of the
A) Memory allocation and garbage collection
B) Database connection pooling
C) Resource initialization and cleanup
D) Thread synchronization
#Python #ContextManagers #ResourceManagement #Advanced
In Python's context managers, what is the purpose of the
__enter__
and __exit__
methods?A) Memory allocation and garbage collection
B) Database connection pooling
C) Resource initialization and cleanup
D) Thread synchronization
#Python #ContextManagers #ResourceManagement #Advanced
Question 7 (Intermediate):
What does the
A) Converts a method into a read-only attribute
B) Marks a function as a class method
C) Enforces type checking on variables
D) Makes a method private
#Python #OOP #Decorators #Intermediate
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What does the
@property
decorator do in Python? A) Converts a method into a read-only attribute
B) Marks a function as a class method
C) Enforces type checking on variables
D) Makes a method private
#Python #OOP #Decorators #Intermediate
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Question 8 (Advanced):
What is the time complexity of checking if an element exists in a Python
A) O(1)
B) O(n)
C) O(log n)
D) O(n^2)
#Python #DataStructures #TimeComplexity #Advanced
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What is the time complexity of checking if an element exists in a Python
set
?A) O(1)
B) O(n)
C) O(log n)
D) O(n^2)
#Python #DataStructures #TimeComplexity #Advanced
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