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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📈 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 68 482 subscribers, ranking 2 406 in the Education category and 4 586 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 482 subscribers.
According to the latest data from 04 November, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -75 over the last 30 days and by 7 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 3.38%. Within the first 24 hours after publication, content typically collects 1.57% reactions from the total number of subscribers.
- Post reach: On average, each post receives 2 314 views. Within the first day, a publication typically gains 1 073 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
- Thematic interests: Content is focused on key topics such as insidead, learning, degree, evaluation, algorithm.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Thanks to the high frequency of updates (latest data received on 05 November, 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.
68 482
Subscribers
+724 hours
-597 days
-7530 days
Posts Archive
🖥 Get Started with Python
A good course on Python from Google.
More than 30 hours of relevant materials that will help you get into the topic.
Here the basic concepts of programming in Python and other features are discussed. Ideal if you have long wanted to try yourself in IT.
📌 Course
http://t.me/codeprogrammer ⭐️
🔒 #Python #COURSES
🗂 A collection of the best free courses
📝 For data science, data engineering, MLOps, ML and GenAI
💠 data science
1️⃣ Python for Everybody Course : A great course for beginners to learn Python.
2️⃣ Data analysis with Python course : This course introduces you to data analysis techniques with Python.
3️⃣ Databases & SQL course : You will learn how to manage databases with SQL.
4️⃣ Intro to Inferential Statistics course : This course teaches you how to make predictions by learning statistics.
5️⃣ ML Zoomcamp course : a practical and practical course for learning machine learning.
🔺 Data engineering
1️⃣ Data Engineering Course : Learn the basics of data engineering.
2️⃣ Data Engineer Learning Path course : a comprehensive road map to become a data engineer.
3️⃣ Database Engineer course : get a specialized degree in database engineering.
4️⃣ Big Data Specialization Course : Get to know big data technologies and their applications.
5️⃣ The Data Eng Zoomcamp course : a practical course to learn data engineering.
🔺 machine learning
1️⃣ Intro to ML course : an introductory and self-paced course to start machine learning.
2️⃣ ML for Everybody course : A simple approach to learning machine learning concepts.
3️⃣ ML in Python course : focus on machine learning with Python and Scikit-Learn.
4️⃣ ML Crash Course : A quick but comprehensive introduction to machine learning.
5️⃣ CS229 : ML : An advanced course for those who want to deepen their knowledge.
🔻 Machine Learning Operations (MLOps)
1️⃣ Python Essentials for MLOps course : an essential course for MLOps enthusiasts..
2️⃣ MLOps for Beginners Course : A great starting point for MLOps newbies.
3️⃣ ML Engineering Course : A set of courses for deep entry into the world of MLOps.
4️⃣ MLOps Specialization Course : Focus on operational aspects of machine learning.
5️⃣ Made With ML course : a special course that combines machine learning with practical applications.
🔹 Generative artificial intelligence
1️⃣ Generative AI for Beginners course : building generative artificial intelligence apps.
2️⃣ Generative AI Fundamentals course : getting to know the basic principles of generative artificial intelligence.
3️⃣ Intro to Gen AI course : from learning large language models to understanding the principles of responsible artificial intelligence.
4️⃣ Generative AI with LLMs course : Learn business applications of artificial intelligence with AWS experts in a practical way.
5️⃣ Generative AI for Everyone course : This course tells you what generative artificial intelligence is, how it works, and what uses and limitations it has.
http://t.me/codeprogrammer ⭐️
☕️ #MachineLearning #Python #COURSES #GenerativeAI #LLM
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Give me your opinion on the design of one of our sites: interact yes 👍 or no 👎
Visit: https://alsheikho.com/
Please check ☑️
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Public APIs
A collective list of API free
GitHub Repo:
https://github.com/public-apis/public-apis
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What if...
- She never forgets your favorite joke?
- She’s always up for a late-night chat?
- She magically understands you (even when you don’t understand yourself)?
Introducing : Design Your Dream AI Girlfriend!
In this fun and quirky session, you'll learn to design AI companions that talk, interact, and maybe even steal your heart. 😜
Register now: https://www.buildfastwithai.com/events/create-your-own-ai-girlfriend
Repost from N/a
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+1
📢 Zuckerberg Releases Free ChatGPT Competitor: Llama 3.1!
Mark Zuckerberg just launched Llama 3.1, a next-gen AI model with the largest dataset ever. Available in 8B, 70B, and 405B versions, it boasts a 128k token context size.
Key Highlights:
• Performance: Outperforms GPT-4o and Claude 3.5 in general knowledge, math, and translation.
• Accessibility: Downloadable by anyone, bringing advanced AI within reach.
• Strategic Move: Meta applies pressure on OpenAI with this open-source release. You probably now understand why OpenAI showed GPT-4o mini a week ago and made it so cheap - soon we will have very smart models that run very fast on any hardware.
Try It Now:
• on Hugging Face: Llama 3.1 on Hugging Face
• on NVIDIA's website: NVIDIA’s website
This release represents a major development in open-source AI, potentially allowing broader access to advanced language models.
https://t.me/DataScienceT ⭐
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