Endi mavjud! Telegram Tadqiqoti 2025 — yilning asosiy insaytlari 
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
Ko'proq ko'rsatish📈 Telegram kanali Machine Learning with Python analitikasi
Machine Learning with Python (@codeprogrammer) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 67 816 obunachidan iborat bo'lib, Taʼlim toifasida 2 417-o'rinni va Hindiston mintaqasida 5 033-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 67 816 obunachiga ega bo‘ldi.
10 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 49 ga, so‘nggi 24 soatda esa -10 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 2.61% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.40% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 1 770 marta ko‘riladi; birinchi sutkada odatda 1 628 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 7 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 11 Iyun, 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.
67 816
Obunachilar
-1024 soatlar
-17 kunlar
+4930 kunlar
Postlar arxiv
10 Must-Know Python Libraries for LLMs in 2025
Large language models (LLMs) are changing the way we think about AI. They help with #chatbots, text generation, and search tools, among other natural language processing tasks and beyond. To work with #LLMs, you need the right #Python libraries.
In this article, we explore 10 of the Python libraries every developer should know in 2025.
Read and learn:
https://machinelearningmastery.com/10-must-know-python-libraries-for-llms-in-2025/
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"Introduction to Python Programming"
This 415-pages #FREE book is perfect if you are starting your #Python journey.
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🔖 The book that paved the way for me to "data science"!
👨🏻💻 "Where do I start now?" This was the first and biggest question I faced when I started my Data Science learning journey!
⏪ I was really overwhelmed by the large number of scattered sources, long courses, and specialized books full of heavy terminology. I didn't know how to start and move forward in this direction...
✔️ But the book Intro to Data Science with Python changed everything for me and gave me a new perspective!
✏️ This book is a complete guide to starting from scratch and is great for both beginners and professionals in this field!! From coding with Python to working with data, visualization, and even AI tools, it explains everything in the simplest and most practical way possible.
💸 A great start for anyone looking to learn data science with Python!👇
┌ 🏳️🌈 Intro to Data Science with Python
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└ 🐱 GitHub-Repos
#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 machine learning 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.
🌟 Link: https://dafriedman97.github.io/mlbook/content/introduction.html
#DataScience #MachineLearning #CheatSheet #stats #analytics #ML #IA #AI #programming #code #rstats #python #deeplearning #DL #CNN #Keras #R https://t.me/CodeProgrammer ✅
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We only accept payments via PayPal and cryptocurrencies.
Contact:
t.me/HusseinSheikho ✅
⚡ Special Offer for 3 Days:
Join our exclusive (paid) channel for a lifetime and get your own bot to download over a million books with daily updates, and a special bot to download more than 80 million scientific articles, all for just $30, a one-time payment only.
The paid channel includes a vast encyclopedia of the most famous books and training courses in all fields of data science and programming languages.
We only accept payments via PayPal and cryptocurrencies.
Contact:
t.me/HusseinSheikho ✅
Special Offer for 3 Days:
Join our exclusive (paid) channel for a lifetime and get your own bot to download over a million books with daily updates, and a special bot to download more than 80 million scientific articles, all for just $30, a one-time payment only.
The paid channel includes a vast encyclopedia of the most famous books and training courses in all fields of data science and programming languages.
We only accept payments via PayPal and cryptocurrencies.
Contact
t.me/HusseinSheikho
Top_100_Machine_Learning_Interview_Questions_Answers_Cheatshee.pdf5.83 MB
Top 100 Machine Learning Interview Questions & Answers Cheatshee
👇👇👇👇👇👇👇👇
The Roadmap for Mastering Language Models in 2025
Link: https://machinelearningmastery.com/the-roadmap-for-mastering-language-models-in-2025/
💠Machine learning
🔸 Deep learning
💠LLM models
https://t.me/Machine_learn
