PyData Careers
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Python Data Science jobs, interview tips, and career insights for aspiring professionals.
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This GitHub repository is a real treasure trove of free programming books.

Here you'll find hundreds of books on topics like #AI, #blockchain, app development, #game development, #Python #webdevelopment, #promptengineering, and many more

GitHub: https://github.com/EbookFoundation/free-programming-books

https://t.iss.one/CodeProgrammer
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Interview Question

What types of file objects are there?

Answer: In Python, file objects are abstractions that provide a unified interface for working with different data sources. They are divided into three types:

▶️Text (TextIO) — work with strings (str) and automatically encode/decode data. For example: open("file.txt", "r", encoding="utf-8").

▶️Binary (BufferedIO) — operate with bytes and are often used for images, videos, or arbitrary data. For example: open("image.jpg", "rb").

▶️Low-level (raw) (RawIO) — provide direct access to devices or files without buffering. Usually used inside the standard library, rarely applied directly.

All these types implement interfaces from io — io.TextIOBase, io.BufferedIOBase, and io.RawIOBase. The standard open() function under the hood returns the appropriate object depending on the mode.


tags: #interview

https://t.iss.one/DataScienceQ
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Interview question

What is a hash table and where is it used in Python?

Answer: A hash table is a data structure that stores key–value pairs and provides fast access by key in time close to O(1).

In Python, the built-in dict and set structures are implemented based on hash tables:

▶️ Keys are hashed using __hash__() and compared via __eq__();

▶️ The hash code is used to compute the index in the array where the element is placed;

▶️ Starting from Python 3.6 (and guaranteed from 3.7), dict preserves the insertion order of keys thanks to the compact dict.

Important: the key must be hashable — that is, have an immutable hash and a consistent implementation of __hash__() and __eq__().


tags: #interview

https://t.iss.one/DataScienceQ
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Interview question

Why is None a singleton object in Python?

Answer: None is the sole instance (singleton) of the NoneType, and all variables containing None refer to the same object. This saves memory because new instances are not created.

tags: #interview

https://t.iss.one/DataScienceQ
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Interview Question

Why doesn't Python support method overloading the way Java or C++ do?

Answer: In Python, all methods are dynamic, and overloading based on their arguments (unlike statically typed languages where the method signature is considered).

Instead of overloading, Python offers:

▶️ Using default argument values

▶️ Using *args and **kwargs for flexible parameter acceptance

▶️ Using @staticmethod or @classmethod if variability is needed

▶️ Using singledispatch functions from functools for type-based handling

tags: #interview

https://t.iss.one/DataScienceQ
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Interview question

Why are int and bool classes, and not "primitive types" as in other languages?

Answer: Because in Python everything is based on the object model. int, bool, str, and others are built-in classes, and each time you use them you create their instances. For example, 5 is an object of the int class.

Even the classes themselves, like int, are also objects. They are created using a special object called type, which is the default metaclass. Therefore, type(int) returns type.


tags: #interview
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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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Interview question

Why are strings immutable in Python?

Answer: Because once a string is created, its value cannot be changed. This ensures that strings can be safely used in hashing, as dictionary keys, and in multithreaded environments without causing data corruption. Instead of modifying the string, Python creates a new string object when any operation changes it. This behavior improves performance and security but requires more memory for frequent modifications.

tags: #interview #python #strings

By: t.iss.one/DataScienceQ 🚀
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Interview question

What is a generator in Python?

Answer: A generator is a special type of function that returns an iterator using the `yield` keyword instead of `return`. It allows you to generate a sequence of values lazily, meaning values are produced on-demand rather than all at once. This saves memory and improves performance when dealing with large datasets.

tags: #python #interview #generator #iterator #programming

By: t.iss.one/DataScienceQ 🚀
Interview question :
What is the Transformer architecture, and why is it considered a breakthrough in NLP?

Interview question :
How does self-attention enable Transformers to capture long-range dependencies in text?

Interview question :
What are the main components of a Transformer model?

Interview question :
Why are positional encodings essential in Transformers?

Interview question :
How does multi-head attention improve Transformer performance compared to single-head attention?

Interview question :
What is the purpose of feed-forward networks in the Transformer architecture?

Interview question :
How do residual connections and layer normalization contribute to training stability in Transformers?

Interview question :
What is the difference between encoder and decoder in the Transformer model?

Interview question :
Why can Transformers process sequences in parallel, unlike RNNs?

Interview question :
How does masked self-attention work in the decoder of a Transformer?

Interview question :
What is the role of key, query, and value in attention mechanisms?

Interview question :
How do attention weights determine which parts of input are most relevant?

Interview question :
What are the advantages of using scaled dot-product attention in Transformers?

Interview question :
How does position-wise feed-forward network differ from attention layers in Transformers?

Interview question :
Why is pre-training important for large Transformer models like BERT and GPT?

Interview question :
How do fine-tuning and transfer learning benefit Transformer-based models?

Interview question :
What are the limitations of Transformers in terms of computational cost and memory usage?

Interview question :
How do sparse attention and linear attention address scalability issues in Transformers?

Interview question :
What is the significance of model size (e.g., number of parameters) in Transformer performance?

Interview question :
How do attention heads in multi-head attention capture different types of relationships in data?

#️⃣ tags: #Transformer #NLP #DeepLearning #SelfAttention #MultiHeadAttention #PositionalEncoding #FeedForwardNetwork #EncoderDecoder

By: t.iss.one/DataScienceQ 🚀
2
Interview question :
What is NumPy, and why is it essential for scientific computing in Python?

Interview question :
How do arrays in NumPy differ from Python lists?

Interview question :
What is the purpose of ndarray in NumPy?

Interview question :
How can you create a 2D array using NumPy?

Interview question :
What does shape represent in a NumPy array?

Interview question :
How do you perform element-wise operations on NumPy arrays?

Interview question :
What is broadcasting in NumPy, and how does it work?

Interview question :
How do you reshape a NumPy array using reshape()?

Interview question :
What is the difference between copy() and view() in NumPy?

Interview question :
How do you concatenate two NumPy arrays along a specific axis?

Interview question :
What is the role of axis parameter in NumPy functions like sum(), mean(), etc.?

Interview question :
How do you find the maximum and minimum values in a NumPy array?

Interview question :
What are ufuncs in NumPy, and give an example?

Interview question :
How do you sort a NumPy array using np.sort()?

Interview question :
What is the use of np.where() in conditional indexing?

Interview question :
How do you generate random numbers using NumPy?

Interview question :
What is the difference between np.random.rand() and np.random.randn()?

Interview question :
How do you load data from a file into a NumPy array?

Interview question :
What is vectorization in NumPy, and why is it important?

Interview question :
How do you calculate the dot product of two arrays in NumPy?

#️⃣ tags: #NumPy #Python #ScientificComputing #Array #ndarray #ElementWiseOperations #Broadcasting #Reshape #CopyView #Concatenation #AxisParameter #MaximumMinimum #ufuncs #Sorting #ConditionalIndexing #RandomNumbers #DataLoading #Vectorization #DotProduct

By: t.iss.one/DataScienceQ 🚀
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 🚀
1
1. What is the primary purpose of PHP?
2. How do you declare a variable in PHP?
3. Which symbol starts a PHP code block?
4. What is the difference between echo and print in PHP?
5. How do you create an array in PHP?
6. Which function is used to get the length of a string in PHP?
7. What is the use of the isset() function in PHP?
8. How do you handle form data in PHP?
9. What does the $_GET superglobal contain?
10. How can you include another PHP file in your script?
11. What is the purpose of the require_once statement?
12. How do you define a function in PHP?
13. What is the difference between == and === in PHP?
14. How do you connect to a MySQL database using PHP?
15. Which function executes a SQL query in PHP?
16. What is the use of the mysqli_fetch_assoc() function?
17. How do you start a session in PHP?
18. What is the purpose of the session_start() function?
19. How do you redirect a user to another page in PHP?
20. What is the use of the header() function in PHP?

#️⃣ #php #webdevelopment #coding #programming #backend #scripting #serverside #dev

By: t.iss.one/DataScienceQ 🚀
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Interview question

What is the output of the following code?
x = [1, 2, 3]
y = x
y.append(4)
print(x)

Answer:
[1, 2, 3, 4]

tags: #python #interview #coding #programming #datastructures #list #mutable #dev

By: t.iss.one/DataScienceQ 🚀
Interview question

What is the output of the following code?
def my_func():
return "hello", "world"

result = my_func()
print(type(result))

Answer:
<class 'tuple'>

tags: #python #interview #coding #programming #function #returnvalues #tuple #dev

By: t.iss.one/DataScienceQ 🚀