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Discover powerful insights with Python, Machine Learning, Coding, and Rβ€”your essential toolkit for data-driven solutions, smart alg

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πŸ“Œ How to Build a Genetic Algorithm from Scratch in Python

πŸ—‚ Category: DATA SCIENCE

πŸ•’ Date: 2024-08-30 | ⏱️ Read time: 16 min read

A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…
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πŸ“Œ Extracting Structured Vehicle Data from Images

πŸ—‚ Category:

πŸ•’ Date: 2025-01-27 | ⏱️ Read time: 10 min read

Build an Automated Vehicle Documentation System that Extracts Structured Information from Images, using OpenAI API,…
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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/

πŸ‘‰ @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

πŸ‘‰ @CODEPROGRAMMER
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800+ SQL Server Interview Questions and Answers .pdf
1 MB
πŸ–₯ 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.

β–ͺ️ GitHub

https://t.me/addlist/8_rRW2scgfRhOTc0 ⚑️
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πŸ“Œ Missing Value Imputation, Explained: A Visual Guide with Code Examples for Beginners

πŸ—‚ Category: MACHINE LEARNING

πŸ•’ 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)

πŸ“– 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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β€œLearn AI” is everywhere. But where do the builders actually start?
Here’s the real path, the courses, papers and repos that matter.


βœ… Videos:

Everything here β‡’ https://lnkd.in/ePfB8_rk

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

βœ… Courses:

All Courses here β‡’ https://lnkd.in/eKKs9ves

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

βœ… Guides:

Access all β‡’ https://lnkd.in/e-GA-HRh

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

βœ… Repos:
➑️ GenAI Agents β†’ https://lnkd.in/eAscvs_i
➑️ Microsoft's AI Agents for Beginners β†’ https://lnkd.in/d59MVgic
➑️ Prompt Engineering Guide β†’ https://lnkd.in/ewsbFwrP
➑️ AI Agent Papers β†’ https://lnkd.in/esMHrxJX

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

Access all β‡’ https://lnkd.in/e-GA-HRh

By: https://t.me/CodeProgrammer 🟑
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πŸ‘¨πŸ»β€πŸ’» This Python library helps you extract usable data for language models from complex files like tables, images, charts, or multi-page documents.

πŸ“ 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.


βœ… Works with PDFs, images, and website links.

β˜‘οΈ Can chunk and process very large documents (up to 1000 pages) by itself.

βœ”οΈ Outputs both JSON and Markdown formats.

β˜‘οΈ Even specifies the exact location of each section on the page.

βœ”οΈ Supports parallel and batch processing.

pip install agentic-doc


β”Œ πŸ₯΅ Agentic Document Extraction
β”œ
🌎 Website
β””
🐱 GitHub Repos

🌐 #DataScience #DataScience
βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–

https://t.me/CodeProgrammer
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πŸ“Ί 12 comprehensive playlists to master
⬅️ machine learning, deep learning, and GenAI!


πŸ‘¨πŸ»β€πŸ’» Each playlist is designed to be simple and understandable for beginners, and then gradually dive deeper into the topics.


πŸ˜‰ Machine Learning Basics (39 videos)

πŸ˜‰ Python for ML (9 videos)

πŸ˜‰ Optimization for ML (5 videos)

πŸ˜‰ Machine Learning with Practical Exercises (37 videos)

πŸ˜‰ Building Decision Trees from Scratch (13 videos)

πŸ˜‰ Building Neural Networks from Scratch (35 videos)

πŸ˜‰ Graph Neural Networks (6 videos)

πŸ˜‰ Computer Vision from Scratch (19 videos)

πŸ˜‰ Building LLM from Scratch (43 videos)

πŸ˜‰ Reasoning in LLMs from Scratch (22 videos)

πŸ˜‰ Building DeepSeek from Scratch (29 videos)

πŸ˜‰ Machine Learning in Production Environment (6 videos)



🌐 #Data_Science #DataScience
βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–

https://t.me/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 πŸš€
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