Python | Machine Learning | Coding | R
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Discover powerful insights with Python, Machine Learning, Coding, and R—your essential toolkit for data-driven solutions, smart alg

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Awesome interactive textbook on probability theory and statistics

Inside are clear visualizations, interactive elements, and minimal dry theory. You can tweak distributions, sample datasets, play with confidence intervals, and clearly see how it all works

Get it here, I recommend opening it on a desktop
https://seeing-theory.brown.edu/

👉 @DataScienceM
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Great find for developers: free cheat sheets on Deep Learning and PyTorch

A detailed guide to creating and training neural networks - link

Basic principles and practice of working with PyTorch - link

👉 @CODEPROGRAMMER
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800+ SQL Server Interview Questions and Answers .pdf
1 MB
🖥 Extremely useful collection of 800+ SQL questions frequently asked in interviews.

It also includes tasks for self-study and many examples.

The collection is perfect for those who want to improve their SQL skills, refresh their knowledge, and test themselves.

▪️ GitHub

https://t.iss.one/addlist/8_rRW2scgfRhOTc0 ⚡️
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📌 Missing Value Imputation, Explained: A Visual Guide with Code Examples for Beginners

🗂 Category: MACHINE LEARNING

🕒 Date: 2024-08-27 | ⏱️ Read time: 13 min read

One (tiny) dataset, six imputation methods?
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Python Cheat Sheet (very very important)

📖 Compact Python cheat sheet covering setup, syntax, data types, variables, strings, control flow, functions, classes, errors, and I/O.

Link: https://discord.com/channels/942740928706281524/1423994784720359567/1424711790947864669
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“Learn AI” is everywhere. But where do the builders actually start?
Here’s the real path, the courses, papers and repos that matter.


Videos:

Everything here ⇒ https://lnkd.in/ePfB8_rk

➡️ LLM Introduction → https://lnkd.in/ernZFpvB
➡️ LLMs from Scratch - Stanford CS229 → https://lnkd.in/etUh6_mn
➡️ Agentic AI Overview →https://lnkd.in/ecpmzAyq
➡️ Building and Evaluating Agents → https://lnkd.in/e5KFeZGW
➡️ Building Effective Agents → https://lnkd.in/eqxvBg79
➡️ Building Agents with MCP → https://lnkd.in/eZd2ym2K
➡️ Building an Agent from Scratch → https://lnkd.in/eiZahJGn

Courses:

All Courses here ⇒ https://lnkd.in/eKKs9ves

➡️ HuggingFace's Agent Course → https://lnkd.in/e7dUTYuE
➡️ MCP with Anthropic → https://lnkd.in/eMEnkCPP
➡️ Building Vector DB with Pinecone → https://lnkd.in/eP2tMGVs
➡️ Vector DB from Embeddings to Apps → https://lnkd.in/eP2tMGVs
➡️ Agent Memory → https://lnkd.in/egC8h9_Z
➡️ Building and Evaluating RAG apps → https://lnkd.in/ewy3sApa
➡️ Building Browser Agents → https://lnkd.in/ewy3sApa
➡️ LLMOps → https://lnkd.in/ex4xnE8t
➡️ Evaluating AI Agents → https://lnkd.in/eBkTNTGW
➡️ Computer Use with Anthropic → https://lnkd.in/ebHUc-ZU
➡️ Multi-Agent Use → https://lnkd.in/e4f4HtkR
➡️ Improving LLM Accuracy → https://lnkd.in/eVUXGT4M
➡️ Agent Design Patterns → https://lnkd.in/euhUq3W9
➡️ Multi Agent Systems → https://lnkd.in/evBnavk9

Guides:

Access all ⇒ https://lnkd.in/e-GA-HRh

➡️ Google's Agent → https://lnkd.in/encAzwKf
➡️ Google's Agent Companion → https://lnkd.in/e3-XtYKg
➡️ Building Effective Agents by Anthropic → https://lnkd.in/egifJ_wJ
➡️ Claude Code Best practices → https://lnkd.in/eJnqfQju
➡️ OpenAI's Practical Guide to Building Agents → https://lnkd.in/e-GA-HRh

Repos:
➡️ GenAI Agents → https://lnkd.in/eAscvs_i
➡️ Microsoft's AI Agents for Beginners → https://lnkd.in/d59MVgic
➡️ Prompt Engineering Guide → https://lnkd.in/ewsbFwrP
➡️ AI Agent Papers → https://lnkd.in/esMHrxJX

Papers:
🟡 ReAct → https://lnkd.in/eZ-Z-WFb
🟡 Generative Agents → https://lnkd.in/eDAeSEAq
🟡 Toolformer → https://lnkd.in/e_Vcz5K9
🟡 Chain-of-Thought Prompting → https://lnkd.in/eRCT_Xwq
🟡 Tree of Thoughts → https://lnkd.in/eiadYm8S
🟡 Reflexion → https://lnkd.in/eggND2rZ
🟡 Retrieval-Augmented Generation Survey → https://lnkd.in/eARbqdYE

Access all ⇒ https://lnkd.in/e-GA-HRh

By: https://t.iss.one/CodeProgrammer 🟡
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👨🏻‍💻 This Python library helps you extract usable data for language models from complex files like tables, images, charts, or multi-page documents.

📝 The idea of Agentic Document Extraction is that unlike common methods like OCR that only read text, it can also understand the structure and relationships between different parts of the document. For example, it understands which title belongs to which table or image.


Works with PDFs, images, and website links.

☑️ Can chunk and process very large documents (up to 1000 pages) by itself.

✔️ Outputs both JSON and Markdown formats.

☑️ Even specifies the exact location of each section on the page.

✔️ Supports parallel and batch processing.

pip install agentic-doc


🥵 Agentic Document Extraction
🌎 Website
🐱 GitHub Repos

🌐 #DataScience #DataScience

https://t.iss.one/CodeProgrammer
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1. What is the output of the following code?
x = [1, 2, 3]
y = x
y.append(4)
print(x)


2. Which of the following data types is immutable in Python?
A) List
B) Dictionary
C) Set
D) Tuple

3. Write a Python program to reverse a string without using built-in functions.

4. What will be printed by this code?
def func(a, b=[]):
b.append(a)
return b

print(func(1))
print(func(2))


5. Explain the difference between == and is operators in Python.

6. How do you handle exceptions in Python? Provide an example.

7. What is the output of:
print(2 ** 3 ** 2)


8. Which keyword is used to define a function in Python?
A) def
B) function
C) func
D) define

9. Write a program to find the factorial of a number using recursion.

10. What does the *args parameter do in a function?

11. What will be the output of:
list1 = [1, 2, 3]
list2 = list1.copy()
list2[0] = 10
print(list1)


12. Explain the concept of list comprehension with an example.

13. What is the purpose of the __init__ method in a Python class?

14. Write a program to check if a given string is a palindrome.

15. What is the output of:
a = [1, 2, 3]
b = a[:]
b[0] = 10
print(a)


16. Describe how Python manages memory (garbage collection).

17. What will be printed by:
x = "hello"
y = "world"
print(x + y)


18. Write a Python program to generate the first n Fibonacci numbers.

19. What is the difference between range() and xrange() in Python 2?

20. What is the use of the lambda function in Python? Give an example.

#PythonQuiz #CodingTest #ProgrammingExam #MultipleChoice #CodeOutput #PythonBasics #InterviewPrep #CodingChallenge #BeginnerPython #TechAssessment #PythonQuestions #SkillCheck #ProgrammingSkills #CodePractice #PythonLearning #MCQ #ShortAnswer #TechnicalTest #PythonSyntax #Algorithm #DataStructures #PythonProgramming

By: @DataScienceQ 🚀
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📌 How To Learn AI (Roadmap)

🗂 Category: ARTIFICIAL INTELLIGENCE

🕒 Date: 2024-08-05 | ⏱️ Read time: 11 min read

A full breakdown of how you can learn AI this year effectively
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1. What is the output of the following code?
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 🚀
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Andrew Ng launches a free course on AI agents 😮

The course covers four key patterns:

Reflection — the agent independently improves its responses

Tool use — using tools

Planning — action planning

Multi-agent collaboration — multiple agents working together on one task
Everything is implemented in pure Python. Andrew emphasizes that creating AI agents is one of the most in-demand skills in the market.

Available here: https://www.deeplearning.ai/courses/agentic-ai/

👉  @codeprogrammer
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