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Data Science & Machine Learning

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
Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expertالشبكة:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expertالهند4 234التعليم2 106

📈 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 75 831 مشتركاً، محتلاً المرتبة 2 106 في فئة التعليم والمرتبة 4 234 في منطقة الهند.

📊 مؤشرات الجمهور والحراك

منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 75 831 مشتركاً.

بحسب آخر البيانات بتاريخ 21 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 770، وفي آخر 24 ساعة بمقدار 8، مع بقاء الوصول العام مرتفعاً.

  • حالة التحقق: غير موثّقة
  • معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 3.15‎%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.09‎% من ردود الفعل نسبةً إلى إجمالي المشتركين.
  • وصول المنشورات: يحصل كل منشور على متوسط 2 385 مشاهدة. وخلال اليوم الأول يجمع عادةً 827 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 22 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.

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Data Science & Machine Learning
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Python for Data Science: The Ultimate Step-by-Step Guide to Learn Python In 7 Days & NLP, Data Science from with Python PDF

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A LITTLE GUIDE TO HANDLING MISSING DATA Having any Feature missing more than 5-10% of its values? you should consider it to be missing data or feature with high absence rate👀 How can you handle these missing values, ensuring you dont loose important part of your data🤷‍♀️ Not a problem😌. Here are important facts you must know😉 ✍️Instances with missing values for all features should be eliminated ✍️Features with high absence rate should either be eliminated or filled with values ✍️Missing values can be replaced using Mean Imputation or Regression Imputation ✍️ Be careful with mean imputation for it may introduce bias as it evens out all instances ✍️Regression Imputation might overfit your model ✍️Mean and Regression Imputation can't be applied to Text features with missing values ✍️Text Features with missing values can be eliminated if not needed in data ✍️Important Text Features with Missing values can be replaced with a new class or category labelled as uncategorized

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Machine_Learning_andrewng.pdf4.01 MB

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To become a Machine Learning Engineer: • Python • numpy, pandas, matplotlib, Scikit-Learn • TensorFlow or PyTorch • Jupyter, Colab • Analysis > Code • 99%: Foundational algorithms • 1%: Other algorithms • Solve problems ← This is key • Teaching = 2 × Learning • Have fun!

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Data Engineering with AWS PDF

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Big data notes.pdf2.89 MB

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#numpy NumPy Smart use of ‘:’ to extract the right shape Sometimes you encounter a 3-dim array that is of shape (N, T, D), while your function requires a shape of (N, D). At a time like this, reshape() will do more harm than good, so you are left with one simple solution: Example: for t in xrange(T): x[:, t, :] = # ...

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📕 Introduction to Machine Learning by Alex Smola and S.V.N. Vishwanathan University Press, Cambridge

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thebook_ Introduction to Machine Learning.pdf10.31 MB

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Pattern Recognition and Machine Learning.pdf4.52 MB

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Pattern Recognition and Machine Learning [ Information Science and Statistics ] Christopher M. Bishop #python #machinelearning #statistics #information #ai #ml

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Follow the latest IT, computer science and entrepreneurship news on Hacker News Digest Telegram channel Hacker News (news.ycombinator.com) – is one of the most influential social news websites. It was here that Drew Houston first introduced Dropbox to the world.   Hacker News Digest Telegram channel will send you the top 10 most popular posts from Hacker News, daily. Subscribe to stay up-to-date!

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SQL handwritten notes .pdf1.37 MB

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Anonymous voting

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Data Visualisation Cheatsheet 🚀

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9 Best Machine Learning Use cases in our Daily Lives 🚀 👓 Youtube Recommendation 👓 Voice Assistants 👓 arrow Smartphone Cam
9 Best Machine Learning Use cases in our Daily Lives 🚀 👓 Youtube Recommendation 👓 Voice Assistants 👓 arrow Smartphone Camera 👓 Google Maps routes 👓 Email Filtering 👓 Search 👓 Translation 👓 Chatbots 👓 Fraud Protection