Forwarded from Python Data Science Jobs & Interviews
1. What is the output of the following code?
2. Which of the following is NOT a valid way to create a dictionary in Python?
A)
B)
C)
D)
3. Write a function that takes a list of integers and returns a new list containing only even numbers.
4. What will be printed by this code?
5. What is the purpose of the
6. Which built-in function can be used to remove duplicates from a list while preserving order?
7. Explain the difference between
8. What does the
9. Write a generator function that yields Fibonacci numbers up to a given limit.
10. What is the output of this code?
11. Which of the following is true about Python’s GIL (Global Interpreter Lock)?
A) It allows multiple threads to execute Python bytecode simultaneously.
B) It prevents race conditions in multithreaded programs.
C) It limits CPU-bound multi-threaded performance.
D) It is disabled in PyPy.
12. How would you implement a context manager using a class?
13. What is the result of
14. Write a recursive function to calculate the factorial of a number.
15. What is the difference between
16. Explain how Python handles memory management for objects.
17. What is the output of this code?
18. Describe the use of
19. Write a program that reads a text file and counts the frequency of each word.
20. What is monkey patching in Python and when might it be useful?
#Python #AdvancedPython #ProgrammingTest #CodingChallenge #PythonInterview #PythonDeveloper #CodeQuiz #HighLevelPython #LearnPython #PythonSkills #PythonExpert
By: @DataScienceQ 🚀
x = [1, 2, 3]
y = x
y[0] = 4
print(x)
2. Which of the following is NOT a valid way to create a dictionary in Python?
A)
dict(a=1, b=2)
B)
{a: 1, b: 2}
C)
dict([('a', 1), ('b', 2)])
D)
{1: 'a', 2: 'b'}
3. Write a function that takes a list of integers and returns a new list containing only even numbers.
4. What will be printed by this code?
def func(a, b=[]):
b.append(a)
return b
print(func(1))
print(func(2))
5. What is the purpose of the
__slots__
attribute in a Python class?6. Which built-in function can be used to remove duplicates from a list while preserving order?
7. Explain the difference between
map()
, filter()
, and reduce()
with examples.8. What does the
@staticmethod
decorator do in Python?9. Write a generator function that yields Fibonacci numbers up to a given limit.
10. What is the output of this code?
import copy
a = [1, 2, [3, 4]]
b = copy.deepcopy(a)
b[2][0] = 5
print(a[2][0])
11. Which of the following is true about Python’s GIL (Global Interpreter Lock)?
A) It allows multiple threads to execute Python bytecode simultaneously.
B) It prevents race conditions in multithreaded programs.
C) It limits CPU-bound multi-threaded performance.
D) It is disabled in PyPy.
12. How would you implement a context manager using a class?
13. What is the result of
bool([])
and why?14. Write a recursive function to calculate the factorial of a number.
15. What is the difference between
is
and ==
in Python?16. Explain how Python handles memory management for objects.
17. What is the output of this code?
class A:
def __init__(self):
self.x = 1
class B(A):
def __init__(self):
super().__init__()
self.y = 2
obj = B()
print(hasattr(obj, 'x') and hasattr(obj, 'y'))
18. Describe the use of
*args
and **kwargs
in function definitions.19. Write a program that reads a text file and counts the frequency of each word.
20. What is monkey patching in Python and when might it be useful?
#Python #AdvancedPython #ProgrammingTest #CodingChallenge #PythonInterview #PythonDeveloper #CodeQuiz #HighLevelPython #LearnPython #PythonSkills #PythonExpert
By: @DataScienceQ 🚀
❤9
Andrew Ng launches a free course on AI agents 😮
The course covers four key patterns:
Available here: https://www.deeplearning.ai/courses/agentic-ai/
👉 @codeprogrammer
The course covers four key patterns:
Reflection — the agent independently improves its responsesEverything is implemented in pure Python. Andrew emphasizes that creating AI agents is one of the most in-demand skills in the market.
Tool use — using tools
Planning — action planning
Multi-agent collaboration — multiple agents working together on one task
Available here: https://www.deeplearning.ai/courses/agentic-ai/
Please open Telegram to view this post
VIEW IN TELEGRAM
❤4
🤖🧠 Join the 5-Day AI Agents Intensive Course with Google
🗓️ 07 Oct 2025
📚 AI News & Trends
Artificial Intelligence is rapidly evolving beyond chatbots and text generation. The next frontier is AI agents — intelligent, autonomous systems that can reason, take action and collaborate with tools and other agents. To help developers and practitioners build these next-generation systems, Google is launching the 5-Day AI Agents Intensive, a no-cost, online program running from ...
#aiagents #dayai #googleartificial #agentsintelligent #ai #evolvingchatbots
🗓️ 07 Oct 2025
📚 AI News & Trends
Artificial Intelligence is rapidly evolving beyond chatbots and text generation. The next frontier is AI agents — intelligent, autonomous systems that can reason, take action and collaborate with tools and other agents. To help developers and practitioners build these next-generation systems, Google is launching the 5-Day AI Agents Intensive, a no-cost, online program running from ...
#aiagents #dayai #googleartificial #agentsintelligent #ai #evolvingchatbots
❤5👍1
🤖🧠 The Little Book of Deep Learning – A Complete Summary and Chapter-Wise Overview
🗓️ 08 Oct 2025
📚 AI News & Trends
In the ever-evolving world of Artificial Intelligence, deep learning continues to be the driving force behind breakthroughs in computer vision, speech recognition and natural language processing. For those seeking a clear, structured and accessible guide to understanding how deep learning really works, “The Little Book of Deep Learning” by François Fleuret is a gem. This ...
#DeepLearning #ArtificialIntelligence #MachineLearning #NeuralNetworks #AIGuides #FrancoisFleuret
🗓️ 08 Oct 2025
📚 AI News & Trends
In the ever-evolving world of Artificial Intelligence, deep learning continues to be the driving force behind breakthroughs in computer vision, speech recognition and natural language processing. For those seeking a clear, structured and accessible guide to understanding how deep learning really works, “The Little Book of Deep Learning” by François Fleuret is a gem. This ...
#DeepLearning #ArtificialIntelligence #MachineLearning #NeuralNetworks #AIGuides #FrancoisFleuret
❤5
Forwarded from Data Science Machine Learning Data Analysis
📌 Understanding Positional Embeddings in Transformers: From Absolute to Rotary
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-20 | ⏱️ Read time: 19 min read
A deep dive into absolute, relative, and rotary positional embeddings with code examples
🗂 Category: DEEP LEARNING
🕒 Date: 2024-07-20 | ⏱️ Read time: 19 min read
A deep dive into absolute, relative, and rotary positional embeddings with code examples
❤5
🤖🧠 Build a Large Language Model From Scratch: A Step-by-Step Guide to Understanding and Creating LLMs
🗓️ 08 Oct 2025
📚 AI News & Trends
In recent years, Large Language Models (LLMs) have revolutionized the world of Artificial Intelligence (AI). From ChatGPT and Claude to Llama and Mistral, these models power the conversational systems, copilots, and generative tools that dominate today’s AI landscape. However, for most developers and learners, the inner workings of these systems remain a mystery until now. ...
#LargeLanguageModels #LLM #ArtificialIntelligence #DeepLearning #MachineLearning #AIGuides
🗓️ 08 Oct 2025
📚 AI News & Trends
In recent years, Large Language Models (LLMs) have revolutionized the world of Artificial Intelligence (AI). From ChatGPT and Claude to Llama and Mistral, these models power the conversational systems, copilots, and generative tools that dominate today’s AI landscape. However, for most developers and learners, the inner workings of these systems remain a mystery until now. ...
#LargeLanguageModels #LLM #ArtificialIntelligence #DeepLearning #MachineLearning #AIGuides
❤3
Forwarded from Data Science Machine Learning Data Analysis
📌 Learn Transformer Fine-Tuning and Segment Anything
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-06-30 | ⏱️ Read time: 13 min read
Train Meta’s SAM to segment high fidelity masks for any domain
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-06-30 | ⏱️ Read time: 13 min read
Train Meta’s SAM to segment high fidelity masks for any domain
❤6
👩🏻💻 Usually, PDF files like financial reports, scientific articles, or data analyses are full of tables, formulas, and complex texts.
┌
├
├
└
➖➖➖➖➖➖➖➖➖➖➖➖
Please open Telegram to view this post
VIEW IN TELEGRAM
❤4👍1
Forwarded from Data Science Jupyter Notebooks
🔥 Trending Repository: Prompt-Engineering-Guide
📝 Description: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
🔗 Repository URL: https://github.com/dair-ai/Prompt-Engineering-Guide
🌐 Website: https://www.promptingguide.ai/
📖 Readme: https://github.com/dair-ai/Prompt-Engineering-Guide#readme
📊 Statistics:
🌟 Stars: 63K stars
👀 Watchers: 668
🍴 Forks: 6.6K forks
💻 Programming Languages: MDX - Jupyter Notebook
🏷️ Related Topics:
==================================
🧠 By: https://t.iss.one/DataScienceM
📝 Description: 🐙 Guides, papers, lecture, notebooks and resources for prompt engineering
🔗 Repository URL: https://github.com/dair-ai/Prompt-Engineering-Guide
🌐 Website: https://www.promptingguide.ai/
📖 Readme: https://github.com/dair-ai/Prompt-Engineering-Guide#readme
📊 Statistics:
🌟 Stars: 63K stars
👀 Watchers: 668
🍴 Forks: 6.6K forks
💻 Programming Languages: MDX - Jupyter Notebook
🏷️ Related Topics:
#deep_learning #openai #language_model #prompt_engineering #generative_ai #chatgpt
==================================
🧠 By: https://t.iss.one/DataScienceM
❤7👍1
Forwarded from Data Science Machine Learning Data Analysis
📌 Mastering Object Counting in Videos
🗂 Category:
🕒 Date: 2024-06-25 | ⏱️ Read time: 8 min read
Step-by-step guide to counting strolling ants on a tree using detection and tracking techniques.
🗂 Category:
🕒 Date: 2024-06-25 | ⏱️ Read time: 8 min read
Step-by-step guide to counting strolling ants on a tree using detection and tracking techniques.
❤5
👨🏻💻 A new tool called Crawl4AI has been introduced that makes Web Scraping and data extraction from websites much easier, faster, and smarter! Especially designed for use in AI models like ChatGPT and similar tools.
┌
└
https://t.iss.one/CodeProgrammer
Please open Telegram to view this post
VIEW IN TELEGRAM
❤6
🤖🧠 Diffusion Transformers with Representation Autoencoders (RAE): The Next Leap in Generative AI
🗓️ 14 Oct 2025
📚 AI News & Trends
Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...
#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
🗓️ 14 Oct 2025
📚 AI News & Trends
Diffusion Transformers (DiTs) have revolutionized image and video generation enabling stunningly realistic outputs in systems like Stable Diffusion and Imagen. However, despite innovations in transformer architectures and training methods, one crucial element of the diffusion pipeline has remained largely stagnant- the autoencoder that defines the latent space. Most current diffusion models still depend on Variational ...
#DiffusionTransformers #RAE #GenerativeAI #StableDiffusion #Imagen #LatentSpace
❤1
Question:
What is type hinting in Python, and how does it enhance code quality?
Answer:👉 @DataScienceQ
What is type hinting in Python, and how does it enhance code quality?
Answer:
Please open Telegram to view this post
VIEW IN TELEGRAM
❤4
Forwarded from Python | Machine Learning | Coding | R
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
┤
┘
Please open Telegram to view this post
VIEW IN TELEGRAM
❤6👍1
🌟 Join @DeepLearning_ai & @MachineLearning_Programming! 🌟
Explore AI, ML, Data Science, and Computer Vision with us. 🚀
💡 Stay Updated: Latest trends & tutorials.
🌐 Grow Your Network: Engage with experts.
📈 Boost Your Career: Unlock tech mastery.
Subscribe Now!
➡️ @DeepLearning_ai
➡️ @MachineLearning_Programming
Step into the future—today! ✨
Explore AI, ML, Data Science, and Computer Vision with us. 🚀
💡 Stay Updated: Latest trends & tutorials.
🌐 Grow Your Network: Engage with experts.
📈 Boost Your Career: Unlock tech mastery.
Subscribe Now!
➡️ @DeepLearning_ai
➡️ @MachineLearning_Programming
Step into the future—today! ✨
❤5
This media is not supported in your browser
VIEW IN TELEGRAM
Instant geodata visualization from the command line
Now you can interactively view raster and vector layers without launching a desktop GIS or Jupyter.
Just run:
Then visualize data with a single command:
Need to customize the display:
These CLI utilities are based on Leafmap, MapLibre, and LocalTileserver and support all formats compatible with rasterio and geopandas.
See here: https://github.com/opengeos/leafmap
👉 @codeprogrammer
Now you can interactively view raster and vector layers without launching a desktop GIS or Jupyter.
Just run:
pip install "leafmap[viewer]"
Then visualize data with a single command:
view-raster /path/to/raster.tif
view-vector /path/to/vector.geojson
Need to customize the display:
view-raster /path/to/raster.tif --band 1 --colormap coolwarm
view-vector /path/to/vector.geojson --style liberty
These CLI utilities are based on Leafmap, MapLibre, and LocalTileserver and support all formats compatible with rasterio and geopandas.
See here: https://github.com/opengeos/leafmap
Please open Telegram to view this post
VIEW IN TELEGRAM
❤8
Please open Telegram to view this post
VIEW IN TELEGRAM
❤3