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

Network:Machine Learning with Python India4 741 Education2 376...

📈 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 68 170 subscribers, ranking 2 376 in the Education category and 4 741 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 170 subscribers.

According to the latest data from 04 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 77 over the last 30 days and by 23 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 2.50%. 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 1 707 views. Within the first day, a publication typically gains 1 071 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 5.
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 September, 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.

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68 170

Subscribers

+2324 hours

+717 days

+7730 days

1 707

Post views

~ 1 07124 hours

~ 1 17048 hours

2.50%

Engagement rate

~ 2

Posts per day

Ads index

beta

Posts Archive

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القناة دى قمة فى الروعة في البرمجة وفيها حوالى 40 دورة انصحكوا تشتركوا فيها 👏💙💞 https://www.youtube.com/channel/UCGbrg29FWhK503HN0KsPkjA?sub_confirmation=1 ودا جروب تليجرام تقدر تحصل فيه كورسات برمجية فى اى مجال حرفيا https://t.me/CISArab لو انت متخصص فى تراك ال PHP Laravel دا جروب رائع https://t.me/phpdevelopers2024 اما لو متخصص فى ال .Net Core فدا جروب عليه مشاريع كبيرة جدا https://t.me/C_Sharp_Developers اما لو بتحب البايثون https://t.me/learncsharp_programing ودا فيديو ازاى تقدر تكسب فلوس وانت طالب https://youtu.be/aqTdGNm9tcg

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🚀 Popular SQL Challenges You Should Know! 🔥1. 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; 📚 More SQL challenges and solutions available here: https://t.me/sql_and_dbt 🚀

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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, excluding purchases Available here (update telegram version): https://t.me/+IucglQVKFK1hN2U6

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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 🔒 💡 #deeplearning #AI #ML #python

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If you can't access the channel, you need to update your Telegram version and buy stars.

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You us stars ⭐️ to support our post ❤️ Use stars ⭐️ only when you think the post deserves it, in order to draw the attention of other friends to read or view the post.

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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: 📷 Create embeddings from videos 🧩 Build a RAG pipeline for data retrieval 💬 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 Intel’s cloud. Enroll Free Here: https://www.deeplearning.ai/short-courses/multimodal-rag-chat-with-videos/ http://t.me/codeprogrammer 🔒 💡 #deeplearning #AI #ML #python

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Our 👑 channel Monthly: 3$ using telegram stars https://t.me/+qvMSLM70zys1ZTJi

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365 data science courses 🟢 probability 🟢 statistics 🟢 git and github 🟢 machine learning 🟢 SQL 🟢 python 🟢 deep learning 🟢 PowerBI 🟢 excel This courses now available in our Paid Channel Access all our paid resources (project course books) for $3 per month. https://t.me/+qvMSLM70zys1ZTJi

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Convert CSV to JSON with Python ⭐️ Github http://t.me/codeprogrammer 🔒 🔒 #deeplearning #AI #ML #python

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Repost from Python Courses & Resources

[Coursera] Deep Learning Specialization What you’ll learn • Build and train deep neural networks, identify key architecture parameters, implement vectorized neural networks and deep learning to applications • Train test sets, analyze variance for DL applications, use standard techniques and optimization algorithms, and build neural networks in TensorFlow • 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 • Build and train RNNs, work with NLP and Word Embeddings, and use HuggingFace tokenizers and transformer models to perform NER and Question Answering Specialization – 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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New world 🌍 programing

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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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Deep Learning NLP AI Python ML Data Mining Tensorflow Keras 👇👇👇👇👇 @Machine_learn

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✂️ CSV Trimming CSV Trimming is a Python package designed to clean up crooked CSVs - the kind you get from parking sites, legacy systems, or poorly collected data - and transform them into clean, well-formatted CSVs with just one line of code. There is no need for complex settings or large language models. pip install csv_trimming

Python
import pandas as pd
from csv_trimming import CSVTrimmer

# Load your csv
csv = pd.read_csv("tests/documents/noisy/sicilia.csv")
# Instantiate the trimmer
trimmer = CSVTrimmer()
# And trim it
trimmed_csv = trimmer.trim(csv)
#That's it!

⭐️ Github http://t.me/codeprogrammer 🔒 🔒 #deeplearning #AI #ML #python