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Machine Learning with Python

Machine Learning with Python

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Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho

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Machine Learning with PythonСітка:Machine Learning with PythonІндія5 047Освіта2 412

📈 Аналітичний огляд Telegram-каналу Machine Learning with Python

Канал Machine Learning with Python (@codeprogrammer) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 67 810 підписників, посідаючи 2 412 місце в категорії Освіта та 5 047 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 67 810 підписників.

За останніми даними від 08 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 50, а за останні 24 години на -5, загальне охоплення залишається високим.

  • Статус верифікації: Не верифікований
  • Рівень залученості (ER): Середній показник залученості аудиторії становить 2.79%. Протягом перших 24 годин після публікації контент зазвичай збирає 2.60% реакцій від загальної кількості підписників.
  • Охоплення публікацій: В середньому кожен допис отримує 1 895 переглядів. Протягом першої доби публікація в середньому набирає 1 764 переглядів.
  • Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 7.
  • Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як insidead, learning, degree, evaluation, algorithm.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho”

Завдяки високій частоті оновлень (останні дані отримано 09 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

67 810
Підписники
-524 години
+227 днів
+5030 день
Архів дописів
Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
Repost from Machine Learning with Python
“Learn AI” is everywhere. But where do the builders actually start? Here’s the real path, the courses, papers and repos that
“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.me/CodeProgrammer 🟡

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Start small and build steady income: learn the basics inside the app, earn your first tokens, and unlock higher rewards as yo
Start small and build steady income: learn the basics inside the app, earn your first tokens, and unlock higher rewards as you progress. Bring friends later to multiply results without extra risk. Start now! #ad InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Think crypto mining is just for whales? Discover how anyone can earn tokens and unlock upgrades and artifacts with Padma Web3
Think crypto mining is just for whales? Discover how anyone can earn tokens and unlock upgrades and artifacts with Padma Web3’s play-to-earn ecosystem. Boost your mana, invite friends, and turn your time into real rewards — no special equipment needed. Curious about the next big thing? See what everyone is mining right now. Start now! #ad InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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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

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Big surprise in our channels on Discord https://discord.gg/PGZku7DrSz

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
Repost from Machine Learning
📌 Missing Value Imputation, Explained: A Visual Guide with Code Examples for Beginners 🗂 Category: MACHINE LEARNING 🕒 Date
📌 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?

Machine Learning with Python
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Repost from Data Analytics
🖥 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.me/addlist/8_rRW2scgfRhOTc0 ⚡️

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
Great find for developers: free cheat sheets on Deep Learning and PyTorch A detailed guide to creating and training neural ne
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

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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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

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
Repost from Machine Learning
📌 Extracting Structured Vehicle Data from Images 🗂 Category: 🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read Build an Autom
📌 Extracting Structured Vehicle Data from Images 🗂 Category: 🕒 Date: 2025-01-27 | ⏱️ Read time: 10 min read Build an Automated Vehicle Documentation System that Extracts Structured Information from Images, using OpenAI API,…

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
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

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
Repost from Machine Learning
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 I spent years chasing success until I found the 7 daily habits no one talks about—now everything’s changed for me. Most people miss the real secret. See what you’ve been overlooking: Success Tips 🔥 | InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Repost from Machine Learning
📌 How to Build a Genetic Algorithm from Scratch in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-30 | ⏱️ Read time: 16 m
📌 How to Build a Genetic Algorithm from Scratch in Python 🗂 Category: DATA SCIENCE 🕒 Date: 2024-08-30 | ⏱️ Read time: 16 min read A complete walkthrough on how one can build a Genetic Algorithm from scratch in Python,…

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Repost from Github Top Repositories
Python library RetinaFace for face detection and working with key points (eyes, nose, mouth) Supports face alignment, easily
Python library RetinaFace for face detection and working with key points (eyes, nose, mouth) Supports face alignment, easily installed via pip install retina-face, and works based on deep models from the insightface project. An excellent tool for tasks in computer vision and face recognition. Usage examples: 
from retinaface import RetinaFace

resp = RetinaFace.detect_faces("img1.jpg")
print(resp)

{
    "face_1": {
        "score": 0.9993440508842468,
        "facial_area": [155, 81, 434, 443],
        "landmarks": {
          "right_eye": [257.82974, 209.64787],
          "left_eye": [374.93427, 251.78687],
          "nose": [303.4773, 299.91144],
          "mouth_right": [228.37329, 338.73193],
          "mouth_left": [320.21982, 374.58798]
        }
  }
}
👉 @DataScienceN

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Creating QR codes with Python in just a few lines of code Anyone can generate their own QR code for a link, text, or even Wi-
Creating QR codes with Python in just a few lines of code Anyone can generate their own QR code for a link, text, or even Wi-Fi data. For this, the qrcode library and the PIL module are used 
pip install qrcode pillow
import qrcode
from PIL import Image

data = input("Enter data for QR: ")
qr = qrcode.QRCode(version=3, box_size=8, border=4)
qr.add_data(data)
qr.make(fit=True)

image = qr.make_image(fill="black", back_color="aqua")
image.save("qr_code.png")
Image.open("qr_code.png")
The output is a ready QR code with any text or link. You can change colors, sizes, and style to fit your design 🙂 👉 https://t.me/CodeProgrammer

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Repost from Machine Learning
📌 A Guide to Clustering Algorithms 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read An overview of c
📌 A Guide to Clustering Algorithms 🗂 Category: DATA SCIENCE 🕒 Date: 2024-09-06 | ⏱️ Read time: 6 min read An overview of clustering and the different families of clustering algorithms.

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
What if you could double your trading power—today? Start with just $200 at Elite Gold Trading, and get a $200 bonus from our
What if you could double your trading power—today? Start with just $200 at Elite Gold Trading, and get a $200 bonus from our partner broker, plus +20% on every future deposit. Don’t wait—join now and copy proven AI strategies in real time. Trade smarter, grow faster, and see real results. Get started here #ad InsideAds

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Repost from Machine Learning
📌 Image Segmentation With K-Means Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read A
📌 Image Segmentation With K-Means Clustering 🗂 Category: MACHINE LEARNING 🕒 Date: 2024-09-05 | ⏱️ Read time: 11 min read An introduction with Python

Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
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Machine Learning with Python
Machine Learning with Pythonverified-telegram-icon
67 813
Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role
Google Collab notebooks to learn everything you need to master prompt engineering with Claude - from basic structure and role prompting to advanced techniques like few-shot learning, avoiding hallucinations, and tool use. Perfect interactive lessons to level up your AI skills Link: https://github.com/anthropics/courses/tree/master/prompt_engineering_interactive_tutorial/Anthropic%201P