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Python Data Science jobs, interview tips, and career insights for aspiring professionals.

Admin: @HusseinSheikho || @Hussein_Sheikho
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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
Question 2 (Advanced):
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 13 (Intermediate):
In NumPy, what is the difference between np.array([1, 2, 3]) and np.array([[1, 2, 3]])?

A) The first is a 1D array, the second is a 2D row vector
B) The first is faster to compute
C) The second automatically transposes the data
D) They are identical in memory usage

#Python #NumPy #Arrays #DataScience

By: https://t.iss.one/DataScienceQ
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🚀 Comprehensive Guide: How to Prepare for a Graph Neural Networks (GNN) Job Interview – 350 Most Common Interview Questions

Read: https://hackmd.io/@husseinsheikho/GNN-interview

#GNN #GraphNeuralNetworks #MachineLearning #DeepLearning #AI #DataScience #PyTorchGeometric #DGL #NodeClassification #LinkPrediction #GraphML

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Forwarded from Code With Python
Python.pdf
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🏳️‍🌈 Notes "Mastering Python"
From Basic to Advanced

👨🏻‍💻 An excellent note that teaches everything from basic concepts to building professional projects with Python.

⭕️ Basic concepts like variables, data types, and control flow

Functions, modules, and writing reusable code

⭕️ Data structures like lists, dictionaries, sets, and tuples

Object-oriented programming: classes, inheritance, and polymorphism

⭕️ Working with files, error handling, and debugging

⬅️ Alongside, with practical projects like data analysis, web scraping, and working with APIs, you learn how to apply Python in the real world.

🌐 #Data_Science #DataScience
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1. What is the primary data structure in pandas?
2. How do you create a DataFrame from a dictionary?
3. Which method is used to read a CSV file in pandas?
4. What does the head() function do in pandas?
5. How can you check the data types of columns in a DataFrame?
6. Which function drops rows with missing values in pandas?
7. What is the purpose of the merge() function in pandas?
8. How do you filter rows based on a condition in pandas?
9. What does the groupby() method do?
10. How can you sort a DataFrame by a specific column?
11. Which method is used to rename columns in pandas?
12. What is the difference between loc and iloc in pandas?
13. How do you handle duplicate rows in pandas?
14. What function converts a column to datetime format?
15. How do you apply a custom function to a DataFrame?
16. What is the use of the apply() method in pandas?
17. How can you concatenate two DataFrames?
18. What does the pivot_table() function do?
19. How do you calculate summary statistics in pandas?
20. Which method is used to export a DataFrame to a CSV file?

#️⃣ #pandas #dataanalysis #python #dataframe #coding #programming #datascience

By: t.iss.one/DataScienceQ 🚀
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