en
Feedback
Machine Learning with Python

Machine Learning with Python

Open in Telegram

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

Show more

📈 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 68 151 subscribers, ranking 2 379 in the Education category and 4 752 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 68 151 subscribers.

According to the latest data from 01 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 84 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 4.17%. Within the first 24 hours after publication, content typically collects 1.54% reactions from the total number of subscribers.
  • Post reach: On average, each post receives 2 845 views. Within the first day, a publication typically gains 1 052 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 02 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.

Buy Ad
68 151
Subscribers
+724 hours
+247 days
+8430 days
Posts Archive
Cheatsheet Machine Learning Algorithms ⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟
Cheatsheet Machine Learning Algorithms ⚡️ BEST DATA SCIENCE CHANNELS ON TELEGRAM 🌟

Update your folder https://t.me/addlist/8_rRW2scgfRhOTc0 Only 10 mins

photo content

#Microsoft launched a #FREE course!!! "Web Development for Beginners" It'll take only 12 weeks to complete. Learn #HTML, #CSS
#Microsoft launched a #FREE course!!!  "Web Development for Beginners" It'll take only 12 weeks to complete. Learn #HTML, #CSS, #JavaScript, #Git, and #GitHub. The course link: https://microsoft.github.io/Web-Dev-For-Beginners/ ⭐️ BEST DATA SCIENCE CHANNELS ON TELEGRAM ⭐️

This channels is for Programmers, Coders, Software Engineers. 0️⃣ Python 1️⃣ Data Science 2️⃣ Machine Learning 3️⃣ Data Visua
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_rRW2scgfRhOTc0https://t.me/Codeprogrammer

Algorithms for Massive Data PDF: https://arxiv.org/pdf/2301.00754 https://t.me/DataScienceM 🌟💯
Algorithms for Massive Data PDF: https://arxiv.org/pdf/2301.00754 https://t.me/DataScienceM 🌟💯

🔐 Bypass any OTP in-call – fully automated! 🌍 Supports all languages 🗣️ Choose between male or female voice 🔁 Accept or reject code during the same call 🤖 Smart human detection + retry logic 📱 Works with: EMAILS, BANKS, WALLETS, 2FA 🎁 Get 2 FREE trial calls before you buy! 🚀 Try it now: @CALL_OTP_MAFIABOT

Discover a New Search Engine 🔍 Find and Join; 💵 Get 50$ ads fee on Waybien. (After 1 May) 💬 Telegram groups/channels 💬 Discord servers 💬 Facebook groups 💬 WhatsApp channels 📲 Join now: @waybien ➡️ Start Searching: www.waybien.com

"Introduction to Probability for Data Science" One of the best books on #Probability. Available FREE. Download the book: prob
+1
"Introduction to Probability for Data Science" One of the best books on #Probability. Available FREE. Download the book: probability4datascience.com/download.html
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras https://t.me/CodeProgrammer

Unlock a treasure trove of knowledge with our exclusive paid channel! For just $2 a month, gain access to thousands of valuable resources, including essential books and premium courses from Coursera and Udemy. Plus, dive into exciting paid projects! Enjoy hassle-free automatic payments via Telegram. Join us today! Link

Stanford's "Design and Analysis of Algorithms" Winter 2025 Lecture Notes & Slides: https://stanford-cs161.github.io/winter202
Stanford's "Design and Analysis of Algorithms" Winter 2025 Lecture Notes & Slides: https://stanford-cs161.github.io/winter2025/lectures/
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras https://t.me/CodeProgrammer

🌟 Join @DeepLearning_ai & @MachineLearning_Programming! 🌟 Explore AI, ML, Data Science, and Computer Vision with us. 🚀 💡
🌟 Join @DeepLearning_ai & @MachineLearning_Programming! 🌟 Explore AI, ML, Data Science, and Computer Vision with us. 🚀 💡 Stay Updated: Latest trends & tutorials. 🌐 Grow Your Network: Engage with experts. 📈 Boost Your Career: Unlock tech mastery. Subscribe Now! ➡️ @DeepLearning_ai ➡️ @MachineLearning_Programming Step into the future—today! ✨

what programming language do you use most often 🌟
what programming language do you use most often 🌟

【DPK-AI Trading】Automatic quantitative system can automatically search for the lowest selling price of digital currencies suc
+1
【DPK-AI Trading】Automatic quantitative system can automatically search for the lowest selling price of digital currencies such as BTC, ETH, USDT, etc. on major exchanges, and quickly purchase them in seconds. 1.DPKAI-quantification, deposits and withdrawals are automatically credited. 2. VIP1-VIP11, quantitative income 20% -35% income. 3. Support multi-currency, smart investment income 25%% up to 40% income. 4. Quantification is reset every 24 hours, and each person can participate in quantitative trading income once a day. 5. Recommend three-level agent invitation rewards, the more invitations, the more rewards, there is no upper limit [A reward 10%, B reward 5%, C reward 3% = 18% reward], send the invitation link to share to your social software, such as: Tiktok, Facebook, Twitter, YouTube, Instagram, WhatsApp group, Telegram group, etc. 【DPK-AI Trading】Registration link: https://dpk-ai.com/#/register?ref=998974 【DPK-AI Trading】Online customer service: https://chat.ssrchat.com/service/gomw2j

"Machine Learning & LLMs for Beginners" Don't miss these 2 books of 100-pages. Both are #FREE to read. 🌟 The Hundred-Page Ma
+1
"Machine Learning & LLMs for Beginners" Don't miss these 2 books of 100-pages. Both are #FREE to read. 🌟 The Hundred-Page Machine Learning Book: themlbook.com/wiki/doku.php 🌟 The Hundred-Page Language Model Book: thelmbook.com
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras https://t.me/CodeProgrammer 🌟

"Data Structures & Algorithms using Python" This book of 222 pages implements all types of #DATASTRUCTURES and #ALGORITHMS. A
+1
"Data Structures & Algorithms using Python" This book of 222 pages implements all types of #DATASTRUCTURES and #ALGORITHMS. And it's 💯 #FREE. Download Free: https://donsheehy.github.io/datastructures/fullbook.pdf By: https://t.me/DataScience4

The latest and the most up-to-date cyber news will be presented on PPHM HACKER NEWS. PPHM subscribers are the first people that receive firsthand cybernews and Tech news. You won't miss any cyber news with us. https://t.me/pphm_HackerNews

Stanford’s Machine Learning - by Andrew Ng A complete lecture notes of 227 pages. Available Free. Download the notes: cs229.s
+1
Stanford’s Machine Learning - by Andrew Ng A complete lecture notes of 227 pages. Available Free. Download the notes: cs229.stanford.edu/main_notes.pdf
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras https://t.me/CodeProgrammer

🔗 Machine Learning from Scratch by Danny Friedman This book is for readers looking to learn new #machinelearning algorithms
🔗 Machine Learning from Scratch by Danny Friedman
This book is for readers looking to learn new #machinelearning algorithms or understand algorithms at a deeper level. Specifically, it is intended for readers interested in seeing machine learning algorithms derived from start to finish. Seeing these derivations might help a reader previously unfamiliar with common algorithms understand how they work intuitively. Or, seeing these derivations might help a reader experienced in modeling understand how different #algorithms create the models they do and the advantages and disadvantages of each one. This book will be most helpful for those with practice in basic modeling. It does not review best practices—such as feature engineering or balancing response variables—or discuss in depth when certain models are more appropriate than others. Instead, it focuses on the elements of those models.
https://dafriedman97.github.io/mlbook/content/introduction.html
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras https://t.me/CodeProgrammer

Introduction to Machine Learning Class Notes by Huy Nguyen https://www.cs.cmu.edu/~hn1/documents/machine-learning/notes.pdf #
+2
Introduction to Machine Learning Class Notes by Huy Nguyen https://www.cs.cmu.edu/~hn1/documents/machine-learning/notes.pdf
#DataAnalytics #Python #SQL #RProgramming #DataScience #MachineLearning #DeepLearning #Statistics #DataVisualization #PowerBI #Tableau #LinearRegression #Probability #DataWrangling #Excel #AI #ArtificialIntelligence #BigData #DataAnalysis #NeuralNetworks #GAN #LearnDataScience #LLM #RAG #Mathematics #PythonProgramming  #Keras https://t.me/CodeProgrammer