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Data science/ML/AI

Data science/ML/AI

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Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatascientist

إظهار المزيد
Programming, data science, ML - free courses by Big Data Specialistالشبكة:Programming, data science, ML - free courses by Big Data Specialistالهند31 693التكنولوجيات والتطبيقات9 381

📈 نظرة تحليلية على قناة تيليجرام Data science/ML/AI

تُعد قناة Data science/ML/AI (@datascience_bds) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 13 667 مشتركاً، محتلاً المرتبة 9 381 في فئة التكنولوجيات والتطبيقات والمرتبة 31 693 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 13 667 مشتركاً.

بحسب آخر البيانات بتاريخ 08 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 150، وفي آخر 24 ساعة بمقدار 4، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 7.97‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 2.27‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 1 089 مشاهدة. وخلال اليوم الأول يجمع عادةً 310 مشاهدة.
  • التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 5.
  • الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل panda, learning, row, api, ethic.

📝 الوصف وسياسة المحتوى

يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Data science and machine learning hub Python, SQL, stats, ML, deep learning, projects, PDFs, roadmaps and AI resources. For beginners, data scientists and ML engineers 👉 https://rebrand.ly/bigdatachannels DMCA: @disclosure_bds Contact: @mldatasci...”

بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 09 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.

13 667
المشتركون
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أرشيف المشاركات
Data science/ML/AI
Data science/ML/AI
13 667
📚 Data Science Riddle Why do CNNs use pooling layers?
Anonymous voting

Data science/ML/AI
Data science/ML/AI
13 667
Why is Kafka Called Kafka❔ Here’s a fun fact that surprises a lot of people. The “Kafka” you use for real-time data pipelines
+1
Why is Kafka Called Kafka❔ Here’s a fun fact that surprises a lot of people. The “Kafka” you use for real-time data pipelines is… named after the novelist Franz Kafka. Why? Jay Kreps (the creator) once explained it simply: - He liked the name. - It sounded mysterious. - And Kafka (the author) wrote a lot. That last part is key. Because Apache Kafka is all about writing: streams of events, logs, and data in motion. So the name stuck. Today, Millions of engineers across the globe talk about “Kafka” every single day… and most don’t realize they’re also invoking a 20th-century novelist. It's funny how small choices like naming your project can shape how the world remembers it.

Data science/ML/AI
Data science/ML/AI
13 667
Cheatsheet: Bayes Theroem And Classifier
Cheatsheet: Bayes Theroem And Classifier

Data science/ML/AI
Data science/ML/AI
13 667
Important LLM Terms 🔹 Transformer Architecture 🔹 Attention Mechanism 🔹 Pre-training 🔹 Fine-tuning 🔹 Parameters 🔹 Self-A
Important LLM Terms 🔹 Transformer Architecture 🔹 Attention Mechanism 🔹 Pre-training 🔹 Fine-tuning 🔹 Parameters 🔹 Self-Attention 🔹 Embeddings 🔹 Context Window 🔹 Masked Language Modeling (MLM) 🔹 Causal Language Modeling (CLM) 🔹 Multi-Head Attention 🔹 Tokenization 🔹 Zero-Shot Learning 🔹 Few-Shot Learning 🔹 Transfer Learning 🔹 Overfitting 🔹 Inference 🔹 Language Model Decoding 🔹 Hallucination 🔹 Latency

Data science/ML/AI
Data science/ML/AI
13 667
📚 Data Science Riddle In a medical diagnosis project, what's more important?
Anonymous voting

Data science/ML/AI
Data science/ML/AI
13 667
Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻 It's easy with Telega.io. As the leadi
Enjoy our content? Advertise on this channel and reach a highly engaged audience! 👉🏻 It's easy with Telega.io. As the leading platform for native ads and integrations on Telegram, it provides user-friendly and efficient tools for quick and automated ad launches. ⚡️ Place your ad here in three simple steps: 1 Sign up 2 Top up the balance in a convenient way 3 Create your advertising post If your ad aligns with our content, we’ll gladly publish it. Start your promotion journey now!

Data science/ML/AI
Data science/ML/AI
13 667
ML models don’t all think alike 🤖 ❇️ Naive Bayes = probability ❇️ KNN = proximity ❇️ Discriminant Analysis = decision bounda
+2
ML models don’t all think alike 🤖 ❇️ Naive Bayes = probability ❇️ KNN = proximity ❇️ Discriminant Analysis = decision boundaries Different paths, same goal: accurate classification. Which one do you reach for first?

Data science/ML/AI
Data science/ML/AI
13 667
📚 Data Science Riddle A dataset has 20% missing values in a critical column. What's the most practical choice?
Anonymous voting

Data science/ML/AI
Data science/ML/AI
13 667
Introduction To Linear Regression
Introduction To Linear Regression

Data science/ML/AI
Data science/ML/AI
13 667
SQL JOINS
SQL JOINS

Data science/ML/AI
Data science/ML/AI
13 667
📚 Data Science Riddle Which Metric is best for imbalanced classification?
Anonymous voting

Data science/ML/AI
Data science/ML/AI
13 667
Machine Learning Cheatsheet
Machine Learning Cheatsheet

Data science/ML/AI
Data science/ML/AI
13 667
Most Common Data Science Skills in Job Posting
Most Common Data Science Skills in Job Posting

Data science/ML/AI
Data science/ML/AI
13 667
📊 Infographic Elements That Every Data Person Should Master 🚀 After years of working with data, I can tell you one thing: �
📊 Infographic Elements That Every Data Person Should Master 🚀 After years of working with data, I can tell you one thing: 👉 The chart ou choose is as important as the data itself. Here’s your quick visual toolkit 👇 🔹 Timelines * Sequential ⏩ great for processes * Scaled ⏳ best for real dates/events 🔹 Circular Charts * Donut 🍩 & Pie 🥧 for proportions * Radial 🌌 for progress or cycles * Venn 🎯 when you want to show overlaps 🔹 Creative Comparisons * Bubble 🫧 & Area 🔵 for impact by size * Dot Matrix 🔴 for colorful distributions * Pictogram 👥 when storytelling matters most 🔹 Classic Must-Haves * Bar 📊 & Histogram 📏 (clear, reliable) * Line 📈 for trends * Area 🌊 & Stacked Area for the “big picture” 🔹 Advanced Tricks * Stacked Bar 🏗 when categories add up * Span 📐 for ranges * Arc 🌈 for relationships 💡 Pro tip from experience: If your audience doesn’t “get it” in 3 seconds, change the chart. The best visualizations speak louder than numbers

Data science/ML/AI
Data science/ML/AI
13 667
INFOGRAPHIC ELEMENTS
INFOGRAPHIC ELEMENTS

Data science/ML/AI
Data science/ML/AI
13 667
📚 Data Science Riddle Why does bagging reduce variance?
Anonymous voting

Data science/ML/AI
Data science/ML/AI
13 667
Big Data 5V
Big Data 5V

Data science/ML/AI
Data science/ML/AI
13 667
Great Packages for R
Great Packages for R

Data science/ML/AI
Data science/ML/AI
13 667
📚 Data Science Riddle Which algorithm is most sensitive to feature scaling?
Anonymous voting

Data science/ML/AI
Data science/ML/AI
13 667
The RAG Developer Stack 2025 - Build Intelligent Al That Thinks, Remembers & Acts
The RAG Developer Stack 2025 - Build Intelligent Al That Thinks, Remembers & Acts