Machine Learning with Python
Kanalga Telegram’da o‘tish
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
Ko'proq ko'rsatish
Tarmoq:📈 Telegram kanali Machine Learning with Python analitikasi
Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 68 117 obunachidan iborat bo'lib, Taʼlim toifasida 2 375-o'rinni va Hindiston mintaqasida 4 809-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 68 117 obunachiga ega bo‘ldi.
26 Avgust, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 120 ga, so‘nggi 24 soatda esa -14 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 4.55% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.02% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 3 099 marta ko‘riladi; birinchi sutkada odatda 1 378 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 5 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent insidead, learning, degree, evaluation, algorithm kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 27 Avgust, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
68 117
Obunachilar
-1424 soatlar
-667 kunlar
+12030 kunlar
Postlar arxiv
Transformer implementations for vision, audio, and AI agents 🤖👁️🎵
Repo: https://github.com/Nicolepcx/transformers-the-definitive-guide
#AI #MachineLearning #Vision #Audio #Agents #Tech
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
Stop. Kill BTTS chaos with our BTTS-NO picks 🚀🔥⚡💰 ONE MARKET. BIG EDGE.
2-day trial = 48h of filtered games (xG, shots, tempo) 🧠📉🛡️
Get the list inside unlock tomorrow’s BTTS-NO shortlist ⚽✅
➡️ Start the 2-day BTTS-NO trial now
#ad 📢 InsideAd
🔥 I send Gold alerts. You copy.
No experience.
No complex charts.
10 minutes/day from your phone.
Join Tania’s Free Academy 👇
#ad 📢 InsideAd
Did you know… unlock Prashant’s daily trade drops 🔒🤝🔥
Not for everyone: I’m leaking what the inner circle watches-3–4 Gold & BTC setups daily with clear SL/targets. 🧠📊
Research from 5,000+ TradingView journals shows traders who pre-plan entries/SL outperform “market chasers” by 31%-get the exact zones inside the XAU/BTC sniper feed. 🎯💥
👉 join the private trade room
#ad 📢 InsideAd
Repost from Machine Learning
🔖 A huge open-source course on AI Engineering from scratch
In the repository, we've collected:
— 435 lessons;
— 320+ hours of content;
— Python, TypeScript, and Rust;
— AI agents, MCP servers, prompts, and AI skills.
Moreover, almost every lesson includes practical tasks, so this isn't just theory, but a full-fledged roadmap for AI Engineering. 🚀
⛓️ Link to the repository
https://github.com/rohitg00/ai-engineering-from-scratch
#AI #MachineLearning #Python #Rust #OpenSource #Tech
✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk
⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A
🔥 I send Gold alerts. You copy.
No experience.
No complex charts.
10 minutes/day from your phone.
Join Tania’s Free Academy 👇
#ad 📢 InsideAd
Unlock the Best Cricket Insights 🌟🏏
One day, I stumbled upon a hidden gem in the world of cricket predictions. It turns out that many fans forget to check the right channels for accurate forecasts and exclusive insights! 📊
Imagine missing out on key match strategies or the game-changing stats that can elevate your fandom to the next level. Don’t be that fan! By joining our channel, you can tap into the insider knowledge that others overlook.
- Get live updates & predictions
- Access exclusive content and analyses
- Connect with fellow cricket enthusiasts
Don’t wait - join now and elevate your cricket experience! 👉 Join Us Today
#ad 📢 InsideAd
LINK DELETED IN 5 MINUTES !
⚡Click HERE and join now to earn 40$ per day ⚡
#ad 📢 InsideAd
Found an easy way to learn math for ML: Mathematics for Machine Learning 🎓📚
This is a curated collection on GitHub, including books, research papers, video lectures, and basic materials on math for studying and reviewing the mathematical foundations of machine learning. 📖📊
It helps build a stronger knowledge base by bringing together trusted resources around topics that machine learning engineers constantly encounter: linear algebra, mathematical analysis, probability theory, statistics, information theory, matrix calculus, and deep learning mathematics. 🧮🤖
Free public repository on GitHub. 💻✨
https://github.com/dair-ai/Mathematics-for-ML
#MachineLearning #Mathematics #DataScience #Learning #GitHub #AI
LINK DELETED IN 5 MINUTES !
⚡Click HERE and join now to earn 40$ per day ⚡
#ad 📢 InsideAd
LINK DELETED IN 5 MINUTES !
⚡Click HERE and join now to earn 40$ per day ⚡
#ad 📢 InsideAd
Repost from Data Analytics
Pandas vs Polars vs DuckDB: Which Library Should You Choose? 🤔📊
pandas remains the default choice for notebooks, exploratory analysis, visualization, and machine learning workflows 📝📈. Polars focus on fast, memory-efficient DataFrame processing ⚡💾, while DuckDB brings a SQL-first approach for querying local files and embedded analytics 🗄️🔍.
Each tool fits a different kind of local data workflow 🛠️. In this article, we compare pandas, Polars, and DuckDB across performance, architecture, interoperability, and real-world use cases 🏆🔗.
More: https://www.analyticsvidhya.com/blog/2026/05/pandas-vs-polars-vs-duckdb/ 🔗
#DataScience #Pandas #Polars #DuckDB #Python #Analytics
Did you know… Steal the “one boring task” AI workflow
Everyone thinks AI wins by adding more tools… but the truth is: a single weekly task can save more time than 10 shiny apps 🤖📉
Inside the latest practical post is the exact format:
task → input → AI step → human review → output 🧩⚙️
The twist: the human review isn’t optional - it’s the part that makes workflows reliable… and most people place it in the wrong spot 😬
👉 Build your first repeatable AI system today
#ad 📢 InsideAdRepost from Machine Learning
🔥 Awesome open-source project to learn more about Transformer Models! 🤖✨
We found this interactive website that shows you visually how transformer models work. 🌐📊
Transformer Explainer:
https://poloclub.github.io/transformer-explainer/
#TransformerModels #OpenSource #AI #MachineLearning #DataScience #Tech
Unlock Practical AI Workflows Did you know that AI is transforming how we manage our tasks? 🚀🔥
From coding agents enhancing enterprise workflows to customer support evolving into AI-driven networks, the future is here! 🤖💡 But… the real question that remains is:
How do you maximize the potential of these AI tools in your daily operations?
- Discover the essential steps to integrate AI seamlessly into your business.
- Understand the shift from simple chatbots to impactful workflows.
- Learn how to define clear processes that keep AI effective and efficient.
Don’t miss out on the insights that could revolutionize your work! 👉 Join the AI Lab
#ad 📢 InsideAd
Did you know… Trade BTC in 60 seconds ⚡️ I just watched a 1‑minute move and wished I’d called it 😅
➡️ Start Sniper Mode now
#ad 📢 InsideAd
"Dive into Deep Learning" 📘🤖 is an open-source book that forms the mathematical foundation for large language models. 🧠📐
It covers linear algebra, mathematical analysis, probability theory, optimization methods, backpropagation, attention mechanisms, and transformer architectures. 🧮📉🔄
The book progressively moves from classical neural networks and convolutional neural networks to modern transformers and practical techniques used in large language models. 🚀🔗🧠
It contains over 1,000 pages 📖 and provides clear explanations, practical examples, and exercises. ✅📝 Making it one of the most comprehensive free resources for understanding the mathematical structure of modern artificial intelligence systems and language models. 🌐🔍🤖
arxiv.org/pdf/2106.11342 🔗
#DeepLearning #AI #MachineLearning #NeuralNetworks #Transformers #OpenSource
Repost from Machine Learning
🚀 Master Binary Classification with Neural Networks! 🧠✨
Ever wondered how to build a neural network from scratch in Python using NumPy? 🐍📊
Binary classification is at the heart of many machine learning applications. 🎯🤖
Our super-detailed guide walks you through the entire process step by step. 📝📚
💡 Dive in and start building your own neural network today! 🏗🔥
https://tinztwinshub.com/data-science/a-beginners-guide-to-developing-an-artificial-neural-network-from-zero/
#MachineLearning #NeuralNetworks #Python #DataScience #AI #Tech
LINK DELETED IN 5 MINUTES !
⚡Click HERE and join now to earn 40$ per day ⚡
#ad 📢 InsideAd
