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Python Programming & AI Resources

Python Programming & AI Resources

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✅ Python Programming Books ✅ Coding Projects ✅ Important Pdfs ✅ Artificial Intelligence Courses ✅ Data Science Notes For promotions: @love_data Buy ads: https://telega.io/c/pythonproz

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📈 Análisis del canal de Telegram Python Programming & AI Resources

El canal Python Programming & AI Resources (@pythonproz) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 13 520 suscriptores, ocupando la posición 9 410 en la categoría Tecnologías y Aplicaciones y el puesto 29 249 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 13 520 suscriptores.

Según los últimos datos del 26 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -91, y en las últimas 24 horas de -11, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 19.06%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 0 visualizaciones. En el primer día suele acumular 0 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
  • Intereses temáticos: El contenido se centra en temas clave como tuple, comprehension, learning, programming, loop.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“✅ Python Programming Books ✅ Coding Projects ✅ Important Pdfs ✅ Artificial Intelligence Courses ✅ Data Science Notes For promotions: @love_data Buy ads: https://telega.io/c/pythonproz”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 27 octubre, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.

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13 520
Suscriptores
-1124 horas
-397 días
-9130 días
Archivo de publicaciones
Complete python handwritten Notes 🚀 React ❤️ For More

Python Handwritten Notes 🐍 React ❤️ For More

Building Chatbots with Python

⌨️ 4 Hidden features of Python
⌨️ 4 Hidden features of Python

✅ 50 Must-Know Python Concepts for Interviews 🐍📊 📍 Core Concepts 1. Data Types: int, float, str, bool, list, tuple, dict, set 2. Operators: Arithmetic, Comparison, Logical 3. Control Flow: if, elif, else 4. Loops: for, while 5. Functions: def, lambda 6. Variables & Scope 📍 Data Structures 7. Lists: Manipulation, indexing, slicing 8. Tuples: Immutability 9. Dictionaries: Key-value pairs 10. Sets: Unique elements 📍 Object-Oriented Programming (OOP) 11. Classes and Objects 12. Inheritance 13. Polymorphism 14. Encapsulation 📍 File Handling 15. Opening, reading, writing files 16. Context Managers (with statement) 📍 Modules & Packages 17. Importing modules 18. Creating and using packages 19. Popular Libraries: NumPy, Pandas, Matplotlib, Scikit-learn 📍 NumPy 20. Arrays: Creation, indexing, slicing 21. Mathematical Operations 22. Broadcasting 📍 Pandas 23. Series and DataFrames 24. Data Selection, Filtering 25. Grouping and Aggregation 26. Joining and Merging 27. Handling Missing Data 📍 Data Cleaning & Preprocessing 28. Handling Missing Values 29. Outlier Detection and Treatment 30. Data Transformation (scaling, normalization) 📍 Data Visualization 31. Matplotlib: Plots, charts, customizations 32. Seaborn: Statistical visualizations 📍 Machine Learning Basics 33. Supervised Learning 34. Unsupervised Learning 35. Model Evaluation Metrics 36. Cross-Validation 📍 Common ML Algorithms 37. Linear Regression 38. Logistic Regression 39. Decision Trees 40. Random Forests 📍 Advanced Concepts 41. List Comprehensions 42. Generators 43. Decorators 44. Error Handling (try, except) 45. Regular Expressions 📍 Best Practices 46. Code Style (PEP 8) 47. Documentation 48. Testing 49. Version Control (Git) 📍 Real-World Scenarios 50. Data Analysis Projects 💡 Tap ❤️ for more! #python #coding #interview #datascience #machinelearning #programming

🚀 AI Journey Contest 2025: Test your AI skills! Join our international online AI competition. Register now for the contest!
🚀 AI Journey Contest 2025: Test your AI skills! Join our international online AI competition. Register now for the contest! Award fund — RUB 6.5 mln! Choose your track: · 🤖 Agent-as-Judge — build a universal “judge” to evaluate AI-generated texts. · 🧠 Human-centered AI Assistant — develop a personalized assistant based on GigaChat that mimics human behavior and anticipates preferences. Participants will receive API tokens and a chance to get an additional 1M tokens. · 💾 GigaMemory — design a long-term memory mechanism for LLMs so the assistant can remember and use important facts in dialogue. Why Join Level up your skills, add a strong line to your resume, tackle pro-level tasks, compete for an award, and get an opportunity to showcase your work at AI Journey, a leading international AI conference. How to Join 1. Register here. 2. Choose your track. 3. Create your solution and submit it by 30 October 2025. 🚀 Ready for a challenge? Join a global developer community and show your AI skills!

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Advanced Python Programming Accelerate your Python programs.pdf8.46 MB

Python Tricks Book.pdf1.27 MB

Learn Python in one day.pdf1.28 MB

Goldman Sachs Python Interview Questions 🚀 🚀 Master Python interviews like a pro! 📌 Must-know questions for every Data Analyst & Python Developer — save & practice now!

Goldman Sachs Python Interview Questions .pdf4.76 MB

DSA in Python 👆👆
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DSA in Python 👆👆

Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻 It's easy with Telega.io. As the leadi
Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻 It's easy with Telega.io. As the leading platform for native ads and integrations on Telegram, it provides user-friendly and efficient tools for quick and automated ad launches. ⚡️ Place your ad here in three simple steps: 1 Sign up 2 Top up the balance in a convenient way 3 Create your advertising post If your ad aligns with our content, we’ll gladly publish it. Start your promotion journey now!

⌨️ Python Tips & Tricks
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⌨️ Python Tips & Tricks

Python_Notes (1).pdf26.85 MB

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Everything you need to learn Python 🧠🐍 React for more ❤️

Python for beginners Notes 🔥 React ❤️ for More

30 Days Python Roadmap for Data Analysts 👆
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30 Days Python Roadmap for Data Analysts 👆

Difference between list and tuple in python 🔸List is mutable ( you can modify the original list) and it's values are written in sqare brackets [ ] 🔸Tuple is immutable ( you can't modify it) and it's values are written in parentheses ( ) delimited by comma( , ) 🔸To convert list to tuple - we use tuple() function list1 = [1,2,3] print(tuple(list1)) Output : (1,2,3) 🔸 For single element list list1 = [1] print(tuple(list1)) Output : (1, ) ▪️a tuple is a tuple because of comma not because of parentheses

71 Python projects with source code