Уже доступно! Исследование Telegram 2025 — ключевые инсайты года 
Machine Learning with Python
Открыть в Telegram
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
Больше📈 Аналитический обзор Telegram-канала Machine Learning with Python
Канал Machine Learning with Python (@codeprogrammer) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 67 829 подписчиков, занимая 2 404 место в категории Образование и 5 049 место в регионе Индия.
📊 Показатели аудитории и динамика
С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 67 829 подписчиков.
Согласно последним данным от 05 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило 77, а за последние 24 часа — 9, при этом общий охват остаётся высоким.
- Статус верификации: Не верифицирован
- Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 2.60%. В первые 24 часа после публикации контент обычно набирает 2.50% реакций от общего числа подписчиков.
- Охват публикаций: В среднем каждый пост получает 1 767 просмотров. В течение первых суток публикация набирает 1 695 просмотров.
- Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 6.
- Тематические интересы: Контент сосредоточен на ключевых темах, таких как insidead, learning, degree, evaluation, algorithm.
📝 Описание и контентная политика
Автор описывает ресурс как площадку для выражения субъективного мнения:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Благодаря высокой частоте обновлений (последние данные получены 06 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Образование.
67 829
Подписчики
+924 часа
+587 дней
+7730 день
Архив постов
Build a Club. Win Cash.
TRAIL by PartBuy
Compete, dominate, get paid. Form your crew, win wars, and split $1,500 with your club. The most competitive game on Telegram.
Ad. 18+
Repost from Udemy Free Coupons
Python Development Professional Certification
Python Development Certification and preparing for other types of certification...
🏷 Category: development
🌍 Language: English (US)
👥 Students: 44,615 students
⭐️ Rating: 4.3/5.0 (925 reviews)
🏃♂️ Enrollments Left: 7
⏳ Expires In: 0D:3H:3M
💰 Price: $9.59 => FREE
🆔 Coupon: 0AEF90A4B22623032313
⚠️ Please note: A verification layer has been added to prevent bad actors and bots from claiming the courses, so it is important for genuine users to enroll manually to not lose this free opportunity.
💎 By: https://t.me/DataScienceC
Build a Club. Win Cash.
TRAIL by PartBuy
Compete, dominate, get paid. Form your crew, win wars, and split $600 with your club. The most competitive game on Telegram.
Ad. 18+
👨🏻💻 6 Free Python Certifications >>>
Python for Beginners -
https://learn.microsoft.com/en-us/shows/intro-to-python-development/
Programming with Python 3. X
https://www.simplilearn.com/free-python-programming-course-skillup
Advanced Python -
https://www.codecademy.com/learn/learn-advanced-python
AI Python for Beginners -
https://www.deeplearning.ai/short-courses/ai-python-for-beginners/
Python Libraries for Data Science -
https://www.simplilearn.com/learn-python-libraries-free-course-skillup
Data Analysis with Python -
https://www.freecodecamp.org/learn/data-analysis-with-python/#data-analysis-with-python-course
Learn more and practice more 👨🏻💻
https://t.me/CodeProgrammer
🚀 Top 25 Machine Learning Architecture Questions (Every ML Engineer Should Know)
Machine Learning isn’t just about training models it’s about designing systems that scale, perform, and survive production.
If you’re preparing for ML interviews, system design rounds, or real-world MLOps work, these are the most important ML Architecture questions you should be comfortable answering
🧠 Core ML Architecture Concepts
1️⃣ What is Machine Learning architecture and why does it matter?
2️⃣ Batch inference vs Real-time inference
3️⃣ What is model serving and common tools used
4️⃣ Data drift: what it is and how to handle it
5️⃣ Feature stores and their role in ML systems
6️⃣ What is MLOps and why it’s critical
⚙️ Training, Optimization & Pipelines
7️⃣ Training vs fine-tuning
8️⃣ Regularization techniques (L1, L2, Dropout, Early stopping)
9️⃣ Model versioning in production
🔟 ML pipelines and workflow automation
1️⃣1️⃣ CI/CD for ML systems
🗄 Data, Embeddings & Databases
1️⃣2️⃣ Choosing the right database for ML
1️⃣3️⃣ What are embeddings and why they’re powerful
1️⃣4️⃣ Handling sensitive data (GDPR, HIPAA, security)
📊 Monitoring, Explainability & Scaling
1️⃣5️⃣ Monitoring tools for ML models
1️⃣6️⃣ Explainability vs Interpretability
1️⃣7️⃣ Horizontal vs Vertical scaling
1️⃣8️⃣ Ensuring reproducibility in ML
1️⃣9️⃣ Factors affecting ML latency
🚢 Deployment & Production Strategies
2️⃣0️⃣ Why Docker/containerization matters
2️⃣1️⃣ GPU-accelerated deployment — when & why
2️⃣2️⃣ A/B testing in ML systems
2️⃣3️⃣ Multi-model deployment strategies
2️⃣4️⃣ Model rollback strategies
2️⃣5️⃣ Designing ML architectures for scalability
Follow the Machine Learning with Python channel on WhatsApp: https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Machine Learning in Python (Course Notes)
I just went through an amazing resource on #MachineLearning in #Python by 365 Data Science, and I had to share the key takeaways with you!
Here’s what you’ll learn:
🔘 Linear Regression - The foundation of predictive modeling
🔘 Logistic Regression - Predicting probabilities and classifications
🔘 Clustering (K-Means, Hierarchical) - Making sense of unstructured data
🔘 Overfitting vs. Underfitting - The balancing act every ML engineer must master
🔘 OLS, R-squared, F-test - Key metrics to evaluate your models
Build a Club. Win Cash.
TRAIL by PartBuy
Compete, dominate, get paid. Form your crew, win wars, and split $600 with your club. The most competitive game on Telegram.
Ad. 18+
Знайшов цікавий сервіс для розробників — ApplicationHubs.
Це платформа, яка дозволяє запускати повноцінне Linux-середовище розробки у хмарі. Можна створити свій Dev Hub, підключитися через SSH, VSCode Remote або JetBrains Gateway і працювати як на звичайному комп'ютері — тільки без налаштування локального середовища.
Підтримуються Docker-проєкти, будь-які мови та фреймворки.
По суті це персональна cloud development machine, яку можна запустити за кілька секунд.
Зараз відкрито ранній доступ (early access).
👉 https://applicationhubs.com
Comment
Посилання на сайт: https://applicationhubs.com/?utm_source=telegram&utm_campaign=collaborator зробити кнопкою з текстом "Спробувати ApplicationHubs"
Publication text
Знайшов цікавий сервіс для розробників — ApplicationHubs.
Це платформа, яка дозволяє запускати повноцінне Linux-середовище розробки у хмарі. Можна створити свій Dev Hub, підключитися через SSH, VSCode Remote або JetBrains Gateway і працювати як на звичайному комп'ютері — тільки без налаштування локального середовища.
Підтримуються Docker-проєкти, будь-які мови та фреймворки.
По суті це персональна cloud development machine, яку можна запустити за кілька секунд.
Зараз відкрито ранній доступ (early access).
[👉 https://applicationhubs.com](https://applicationhubs.com/?utm_source=telegram&utm_campaign=collaborator)
🎁 23 Years of SPOTO – Claim Your Free IT Certs Prep Kit!
🔥Whether you're preparing for #Python, #AI, #Cisco, #PMI, #Fortinet, #AWS, #Azure, #Excel, #comptia, #ITIL, #cloud or any other in-demand certification – SPOTO has got you covered!
✅ Free Resources :
・Free Python, Excel, Cyber Security, Cisco, SQL, ITIL, PMP, AWS courses: https://bit.ly/4lk4m3c
・IT Certs E-book: https://bit.ly/4bdZOqt
・IT Exams Skill Test: https://bit.ly/4sDvi0b
・Free AI material and support tools: https://bit.ly/46TpsQ8
・Free Cloud Study Guide: https://bit.ly/4lk3dIS
🎁 Join SPOTO 23rd anniversary Lucky Draw:
📱 iPhone 17
🛒free order
🛒 Amazon Gift Card $50/$100
📘 AI/CCNA/PMP Course Training + Study Material + eBook
Enter the Draw 👉: https://bit.ly/3NwkceD
👉 Become Part of Our IT Learning Circle! resources and support:
https://chat.whatsapp.com/Cnc5M5353oSBo3savBl397
💬 Want exam help? Chat with an admin now!
wa.link/rozuuw
⏰Last Chance – Get It Before It’s Gone!
Repost from Learn Python Coding
The Ultimate 2026 Python Learning Roadmap: From Beginner to Expert
Start learning #Python in 2026 with a clear, structured #roadmap that takes you from beginner to expert. Build real-world skills through hands-on projects, master essential libraries, and prepare for in-demand careers in data science, web development, and #AI
Start: https://www.coursera.org/resources/python-learning-roadmap
Post Text:
Why pay $20 for each AI when you can access 90+ AI tools for the price of a single subscription?
The ultimate "Swiss Army Knife" of the AI world!
Why it’s a game-changer:
✅ All the top models in one place: ChatGPT-4o, Midjourney, Claude 3.5, Gemini, Nano Banana 2, and more.
✅ Convenience: Work via your browser or directly through the Telegram bot.
✅ No limits: Runs smoothly without a VPN, with flexible payment options.
Why you can trust it:
👥 Community: 700,000+ users on Telegram.
🎓 Free Academy: Video tutorials included (perfect even for beginners).
🎥 Expert Content: Dedicated YouTube channel with deep dives.
Stop collecting subscriptions. Switch to the unified standard for AI access.
Hyperlink for the admin:
Text: Try it now
Link: https://syntx.ai/welcome/Hob0w8sZ
Repost from Learn Python Coding
This channels is for Programmers, Coders, Software Engineers.
0️⃣ Python
1️⃣ Data Science
2️⃣ Machine Learning
3️⃣ Data Visualization
4️⃣ Artificial Intelligence
5️⃣ Data Analysis
6️⃣ Statistics
7️⃣ Deep Learning
8️⃣ programming Languages
✅ https://t.me/addlist/8_rRW2scgfRhOTc0
✅ https://t.me/Codeprogrammer
🧠 Python libraries for AI agents - complexity of learning 🔥
🟢 Easy
• LangChain
• tool calling
• agent memory
• simple agents
• CrewAI
• agents with roles
• collaboration of several agents
• SmolAgents
• lightweight agents
• quick experiments
🟡 Medium
• LangGraph
• stateful workflow
• agent orchestration
• LlamaIndex
• RAG pipelines
• data indexing
• knowledge agents
• OpenAI Agents SDK
• tool integrations
• agent workflows
• Strands
• agent orchestration
• task coordination
• Semantic Kernel
• skills / plugins
• AI process orchestration
• PydanticAI
• typed LLM applications
• structured agent workflows
• Langroid
• message exchange between agents
• interaction with tools
🔴 Difficult
• AutoGen
• multi-agent dialogues
• autonomous agent cooperation
• DSPy
• programmable prompting
• optimization of LLM pipelines
• A2A
• agent-to-agent protocol
• distributed agent systems
https://t.me/CodeProgrammer ✅
🌟 Looking to promote your Telegram channel — without paying a cent? Join our free, community-driven promotion system powered by @PromochannelAssistantbot! Get real exposure, real users, and a transparent verification process designed to protect everyone.
No paid promo. No risks. Just a smarter way to grow. 🙌
🌱 What Makes This Bot Different
• All promotions are 100% free • Every channel is verified for authenticity • No fake numbers — only real engagement • Promo packs are fair: channels are grouped by size • Weekly drops give your channel consistent visibility
If you want growth that lasts, this is the place to start. 📈
📘 How to Add Your Channel (Step-by-Step Guide)
• Submit your channel for verification. • After approval, it’s added to a size-matched promo pack. • Customize your button name for better visibility. • Weekly promo drops last 24 hours and bring real users.
Join a transparent, safe, and supportive growth ecosystem. 💙 Start now → @PromochannelAssistantbot
#ad InsideAds
ML Engineer, LLM Engineer, take note: TorchCode
A platform with practice tasks for basic implementations in PyTorch and questions on Transformer, which are often encountered in interviews.
→ Gathers in 39 structured tasks typical for #ML #interviews - implementations of operators, modules, and architectures in #PyTorch.
→ Provides auto-checking, gradient checking, time measurement, and instant feedback, so that the practice more closely resembles #LeetCode for interviews.
→ Built on the basis of Jupyter Notebook, while supporting one-click reset, hints, reference solutions, and progress tracking.
→ Covers such frequent topics as ReLU, Softmax, LayerNorm, Attention, RoPE, Flash Attention, #LoRA, $MoE, and others.
→ Supports online mode via Hugging Face Spaces, opening individual tasks in #Google #Colab, and local launch via #Docker.
👉 https://github.com/duoan/TorchCode
