متاح الآن! بحث تيليغرام 2025 — أهم رؤى العام 
Data Science & Machine Learning
الذهاب إلى القناة على Telegram
Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free For collaborations: @love_data
إظهار المزيد📈 نظرة تحليلية على قناة تيليجرام Data Science & Machine Learning
تُعد قناة Data Science & Machine Learning (@datasciencefun) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 75 837 مشتركاً، محتلاً المرتبة 2 107 في فئة التعليم والمرتبة 4 219 في منطقة الهند.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 75 837 مشتركاً.
بحسب آخر البيانات بتاريخ 22 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 728، وفي آخر 24 ساعة بمقدار -2، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 3.00%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.05% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 2 278 مشاهدة. وخلال اليوم الأول يجمع عادةً 794 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 3.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل learning, accuracy, distribution, panda, dataset.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Join this channel to learn data science, artificial intelligence and machine learning with funny quizzes, interesting projects and amazing resources for free
For collaborations: @love_data”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 23 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.
75 837
المشتركون
-224 ساعات
+637 أيام
+72830 أيام
أرشيف المشاركات
Adaptive_Computation_and_Machine_Learning_Ralf_Herbrich_Learning.pdf2.69 MB
Some interview questions related to Data science
1- what is difference between structured data and unstructured data.
2- what is multicollinearity.and how to remove them
3- which algorithms you use to find the most correlated features in the datasets.
4- define entropy
5- what is the workflow of principal component analysis
6- what are the applications of principal component analysis not with respect to dimensionality reduction
7- what is the Convolutional neural network. Explain me its working
👋 Welcome to @datastructuresandalgoofficial 👋
To get job in top tech companies like 𝙂𝙤𝙤𝙜𝙡𝙚, 𝘼𝙢𝙖𝙯𝙤𝙣, 𝙈𝙞𝙘𝙧𝙤𝙨𝙤𝙛𝙩, 𝙁𝙖𝙘𝙚𝙗𝙤𝙤𝙠, 𝙚𝙩𝙘 you must know 𝘿𝙖𝙩𝙖 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚𝙨 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙨. And for excelling in tech field you should know 𝘿𝙖𝙩𝙖 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚𝙨 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙨.
In this Channel you will get all materials related Data Structures and Algorithms(DSA).
𝙁𝙤𝙧 𝙡𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝘿𝙖𝙩𝙖 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚𝙨 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙨(𝘿𝙎𝘼) 𝙛𝙤𝙧 𝙛𝙧𝙚𝙚 𝙟𝙤𝙞𝙣 𝙤𝙪𝙧 𝙩𝙚𝙡𝙚𝙜𝙧𝙖𝙢 𝙘𝙝𝙖𝙣𝙣𝙚𝙡:
https://t.me/datastructuresandalgoofficial
So what are you waiting for?
Join right now👍
https://t.me/datastructuresandalgoofficial
👋 Welcome to @datastructuresandalgoofficial 👋
To get job in top tech companies like 𝙂𝙤𝙤𝙜𝙡𝙚, 𝘼𝙢𝙖𝙯𝙤𝙣, 𝙈𝙞𝙘𝙧𝙤𝙨𝙤𝙛𝙩, 𝙁𝙖𝙘𝙚𝙗𝙤𝙤𝙠, 𝙚𝙩𝙘 you must know 𝘿𝙖𝙩𝙖 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚𝙨 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙨. And for excelling in tech field you should know 𝘿𝙖𝙩𝙖 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚𝙨 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙨.
In this Channel you will get all materials related Data Structures and Algorithms(DSA).
𝙁𝙤𝙧 𝙡𝙚𝙖𝙧𝙣𝙞𝙣𝙜 𝘿𝙖𝙩𝙖 𝙎𝙩𝙧𝙪𝙘𝙩𝙪𝙧𝙚𝙨 𝙖𝙣𝙙 𝘼𝙡𝙜𝙤𝙧𝙞𝙩𝙝𝙢𝙨(𝘿𝙎𝘼) 𝙛𝙤𝙧 𝙛𝙧𝙚𝙚 𝙟𝙤𝙞𝙣 𝙤𝙪𝙧 𝙩𝙚𝙡𝙚𝙜𝙧𝙖𝙢 𝙘𝙝𝙖𝙣𝙣𝙚𝙡:
https://t.me/datastructuresandalgoofficial
So what are you waiting for?
Join right now👍
https://t.me/datastructuresandalgoofficial
Free Data Science courses from Udemy and Udacity
👇👇
Intro to Data Science
https://imp.i115008.net/rn2beD
Data Analysis and Visualization
https://imp.i115008.net/JrBjZR
Data Analysis with R by Facebook
https://imp.i115008.net/gbJr5r
Introduction to Data Science using Python
https://ern.li/OP/1qvkxbfaxqj
Intro to Data for Data Science
https://ern.li/OP/1qvkxbfbmf8
Data Science with Analogies, Algorithms and Solved Problems
https://ern.li/OP/1qvkxbfcehz
Introduction to Data Science for Complete Beginners
https://bit.ly/3sh4oPO
ENJOY LEARNING 👍👍
Source codes for data science projects 👇👇
1. Build chatbots:
https://dzone.com/articles/python-chatbot-project-build-your-first-python-pro
2. Credit card fraud detection:
https://www.kaggle.com/renjithmadhavan/credit-card-fraud-detection-using-python
3. Fake news detection
https://data-flair.training/blogs/advanced-python-project-detecting-fake-news/
4.Driver Drowsiness Detection
https://data-flair.training/blogs/python-project-driver-drowsiness-detection-system/
5. Recommender Systems (Movie Recommendation)
https://data-flair.training/blogs/data-science-r-movie-recommendation/
6. Sentiment Analysis
https://data-flair.training/blogs/data-science-r-sentiment-analysis-project/
7. Gender Detection & Age Prediction
https://www.pyimagesearch.com/2020/04/13/opencv-age-detection-with-deep-learning/
𝗘𝗡𝗝𝗢𝗬 𝗟𝗘𝗔𝗥𝗡𝗜𝗡𝗚👍👍
Digital transformation started a shift to remote work and so did the conferences.
All major events in IT conferencing world now have online block or are fully online.Stay tuned and never miss a major event in IT conferencing world with https://t.me/getconf.
Upcoming online and offline conferences announcements, various themes, ticket pricing and more!
Data Science from Scratch- First Principles with Python.pdf5.57 MB
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Practical_Machine_Learning_and_Image_Processing_For_Facial_Recognition.pdf4.78 MB
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OpenCV_Computer_Vision_with_Python_Learn_to_capture_videos,_manipulate.pdf3.74 MB
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