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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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๐Ÿ“ˆ Analytical overview of Telegram channel Machine Learning with Python

Channel Machine Learning with Python (@codeprogrammer) in the English language segment is an active participant. Currently, the community unites 67 815 subscribers, ranking 2 419 in the Education category and 5 033 in the India region.

๐Ÿ“Š Audience metrics and dynamics

Since its creation on ะฝะตะฒั–ะดะพะผะพ, the project has demonstrated rapid growth, gathering an audience of 67 815 subscribers.

According to the latest data from 12 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 57 over the last 30 days and by 3 over the last 24 hours, overall reach remains high.

  • Verification status: Not verified
  • Engagement rate (ER): The average audience engagement rate is 4.13%. Within the first 24 hours after publication, content typically collects 1.69% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 799 views. Within the first day, a publication typically gains 1 149 views.
  • Reactions and interaction: The audience actively supports content: the average number of reactions per post is 6.
  • Thematic interests: Content is focused on key topics such as insidead, learning, degree, evaluation, algorithm.

๐Ÿ“ Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
โ€œLearn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikhoโ€

Thanks to the high frequency of updates (latest data received on 13 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.

67 815
Subscribers
+324 hours
-187 days
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Posts Archive
Data Science Cheat Sheets Quick help to make a data scientist's life easier โœ… http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ’ก #deeplearning #AI #ML #python

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Data Science Cheat Sheets Quick help to make a data scientist's life easier About Dataset A collection of cheat sheets for va
Data Science Cheat Sheets Quick help to make a data scientist's life easier About Dataset A collection of cheat sheets for various data-science related languages and topics http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ’ก #deeplearning #AI #ML #python

Andrew Ng just released two new AI Python courses for beginners! The course teaches how to write code using AI. If you're thi
Andrew Ng just released two new AI Python courses for beginners! The course teaches how to write code using AI. If you're thinking about learning to code, now is the perfect time to do so. https://deeplearning.ai/short-courses/ai-python-for-beginners/ http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ’ก #deeplearning #AI #ML #python

Coursera has launched a collaboration with the MAJOR platform to enable students to self-fund using the MAJOR platform. Students can now access free Coursera scholarships through MAJOR. Don't miss the opportunity: Click here.

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ุงู„ู‚ู†ุงุฉ ุฏู‰ ู‚ู…ุฉ ูู‰ ุงู„ุฑูˆุนุฉ ููŠ ุงู„ุจุฑู…ุฌุฉ ูˆููŠู‡ุง ุญูˆุงู„ู‰ 40 ุฏูˆุฑุฉ ุงู†ุตุญูƒูˆุง ุชุดุชุฑูƒูˆุง ููŠู‡ุง ๐Ÿ‘๐Ÿ’™๐Ÿ’ž https://www.youtube.com/channel/UCGbrg29FWhK503HN0KsPkjA?sub_confirmation=1 ูˆุฏุง ุฌุฑูˆุจ ุชู„ูŠุฌุฑุงู… ุชู‚ุฏุฑ ุชุญุตู„ ููŠู‡ ูƒูˆุฑุณุงุช ุจุฑู…ุฌูŠุฉ ูู‰ ุงู‰ ู…ุฌุงู„ ุญุฑููŠุง https://t.me/CISArab ู„ูˆ ุงู†ุช ู…ุชุฎุตุต ูู‰ ุชุฑุงูƒ ุงู„ PHP Laravel ุฏุง ุฌุฑูˆุจ ุฑุงุฆุน https://t.me/phpdevelopers2024 ุงู…ุง ู„ูˆ ู…ุชุฎุตุต ูู‰ ุงู„ .Net Core ูุฏุง ุฌุฑูˆุจ ุนู„ูŠู‡ ู…ุดุงุฑูŠุน ูƒุจูŠุฑุฉ ุฌุฏุง https://t.me/C_Sharp_Developers ุงู…ุง ู„ูˆ ุจุชุญุจ ุงู„ุจุงูŠุซูˆู† https://t.me/learncsharp_programing ูˆุฏุง ููŠุฏูŠูˆ ุงุฒุงู‰ ุชู‚ุฏุฑ ุชูƒุณุจ ูู„ูˆุณ ูˆุงู†ุช ุทุงู„ุจ https://youtu.be/aqTdGNm9tcg

๐Ÿš€ Popular SQL Challenges You Should Know! ๐Ÿ”ฅ1. How to Find the Second Highest Value in a Column  Need to find the second highest salary? Use a combination of ORDER BY and LIMIT to get it easily: SELECT MAX(salary) AS second_highest_salary FROM employees WHERE salary < (SELECT MAX(salary) FROM employees); 2. How to Find the N-th Highest Salary in a Table  Want to find the N-th highest salary? Just order the salaries in descending order and use LIMIT to pick the exact one you need. For example, to find the 3rd highest salary: SELECT salary FROM employees ORDER BY salary DESC LIMIT 2,1; ๐Ÿ“š More SQL challenges and solutions available here: https://t.me/sql_and_dbt ๐Ÿš€

Repost from Data Science Books
Ace the data science interview The book that deserves a thousand stars and more than 100 thousand requests for this book, exc
Ace the data science interview The book that deserves a thousand stars and more than 100 thousand requests for this book, excluding purchases Available here (update telegram version): https://t.me/+IucglQVKFK1hN2U6

Building Agents: Free Course We just released a course with > 20 videos & notebooks focused on building agents. All code is o
Building Agents: Free Course We just released a course with > 20 videos & notebooks focused on building agents. All code is open-source and the course is free! Context Back in June, I gave at talk at @aiDotEngineer on building agents with LangGraph. I got ~2 hrs of questions. We took these questions along with lots of feedback we've heard from users and built a course! Module 1: Foundations The first module includes several notebooks & videos that focus on what is an agent explained in simple terms, how to build various types of agents (routers, ReAct, etc), how to debug them w LangGraph Studio, and how to deploy them w LangGraph Cloud. Module 2: Memory One of the biggest questions we've heard is how to build long-running agents, which can remember important details. We show how memory works with LangGraph, and how to use various databases (SQLite, Postgres) to serve as agent memory. Module 3: Human-In-The-Loop Another central question with agents is allowing humans to approve actions (tools use) or modify the agent state (add feedback). We show various human in the loop interaction patterns that are supported in LangGraph, and also show how to stream the graph state during agent execution for human review. Module 4: Controllability The final module focuses on various design patterns for agent control flow, including parallelization of tasks and creating multi-agent teams with their own tasks / internal memory. This builds up into a customizable multi agent system for research that pulls together themes from the entire course. Course (links to code, all videos): https://academy.langchain.com/courses/intro-to-langgraph http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ’ก #deeplearning #AI #ML #python

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You us stars โญ๏ธ to support our post โค๏ธ Use stars โญ๏ธ only when you think the post deserves it, in order to draw the attention of other friends to read or view the post.

New course with @Intel! Multimodal RAG: Chat with Videos is available starting today! Learn from @Vasudev_Lal to build an AI chat system that answers questions from video content! Learn to: ๐Ÿ“ท Create embeddings from videos ๐Ÿงฉ Build a RAG pipeline for data retrieval ๐Ÿ’ฌ Use Large Vision-Language Models (LVLMs) for Q&A using both text and image inputs. In this course, you will make API calls to access multimodal models hosted by @PredictionGuard on Intelโ€™s cloud. Enroll Free Here: https://www.deeplearning.ai/short-courses/multimodal-rag-chat-with-videos/ http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ’ก #deeplearning #AI #ML #python

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Convert CSV to JSON with Python โญ๏ธ Github http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ”’ #deeplearning #AI #ML #python
Convert CSV to JSON with Python โญ๏ธ Github http://t.me/codeprogrammer ๐Ÿ”’ ๐Ÿ”’ #deeplearning #AI #ML #python

[Coursera] Deep Learning Specialization What youโ€™ll learn โ€ข Build and train deep neural networks, identify key architecture p
[Coursera] Deep Learning Specialization What youโ€™ll learn โ€ข Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications โ€ข Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow โ€ข Build a CNN and apply it to detection and recognition tasks, use neural style transfer to generate art, and apply algorithms to image and video data โ€ข Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering Specialization โ€“ 5 course series 1. Neural Networks and Deep Learning 2. Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization 3. Structuring Machine Learning Projects 4. Convolutional Neural Networks 5. Sequence Models Available free in our Paid Channel https://t.me/+qvMSLM70zys1ZTJi

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