fa
Feedback

فریب کلاهبرداران را نخورید! تل‌متریو این کانال‌ها را شناسایی و برچسب‌گذاری می‌کند 👉 برای مشاهده برچسب، اشتراک تهیه کنید

Data Science & Machine Learning

Data Science & Machine Learning

رفتن به کانال در 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

نمایش بیشتر
شبکه: Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Exشبکه: Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expertالهند3 828آموزش2 011

📈 تحلیل کانال تلگرام Data Science & Machine Learning

کانال Data Science & Machine Learning (@datasciencefun) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 77 681 مشترک است و جایگاه 2 011 را در دسته آموزش و رتبه 3 828 را در منطقه الهند دارد.

📊 شاخص‌های مخاطب و پویایی

از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 77 681 مشترک جذب کرده است.

بر اساس آخرین داده‌ها در تاریخ 10 نوامبر, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -93 و در ۲۴ ساعت گذشته برابر -5 بوده و همچنان دسترسی گسترده‌ای حفظ شده است.

  • وضعیت تأیید: تأیید نشده
  • نرخ تعامل (ER): میانگین تعامل مخاطب 3.28% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 0.99% واکنش نسبت به کل مشترکان کسب می‌کند.
  • دسترسی پست‌ها: هر پست به طور میانگین 2 549 بازدید دریافت می‌کند. در اولین روز معمولاً 767 بازدید جمع‌آوری می‌شود.
  • واکنش‌ها و تعامل: مخاطبان به‌طور فعال حمایت می‌کنند؛ میانگین واکنش به هر پست 3 است.
  • علایق موضوعی: محتوا بر موضوعات کلیدی مانند learning, accuracy, distribution, panda, dataset تمرکز دارد.

📝 توضیح و سیاست محتوایی

نویسنده این فضا را محل بیان دیدگاه‌های شخصی توصیف می‌کند:
“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”

به لطف به‌روزرسانی‌های پرتکرار (آخرین داده در تاریخ 11 نوامبر, 2026)، کانال همواره به‌روز و دارای دسترسی بالاست. تحلیل‌ها نشان می‌دهد مخاطبان به‌طور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته آموزش تبدیل کرده‌اند.

Buy Ad
77 681
مشترکین
-524 ساعت
-377 روز
-9330 روز
آرشیو پست ها
Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Data Science Interview Questions and Answers 👨‍💻.pdf13.81 MB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
The Data Science Handbook Carl Shan, 2015

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
ML_Projects_270.pdf3.69 KB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
devops-1.pdf1.91 MB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Pandas loc & iloc Function.pdf0.50 KB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
SparkNotes.pdf2.30 KB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
+1
Foundational Python for Data Science.pdf26.26 MB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
🚀Join us this week in the FREE Webinars and explore the fields of tech! You will find the answers to all your questions at o
🚀Join us this week in the FREE Webinars and explore the fields of tech! You will find the answers to all your questions at our webinars. Open the link https://crst.co/Dxfog, make your choice and apply now while there are still seats available. See you there! ▶️ December 12 - Most In-Demand IT Jobs 2023: Become a Systems Engineer ▶️ December 13 - Tech Jobs for Beginners: Become a Software Tester ▶️ December 15 - Most In-Demand IT Jobs 2023: Become a Software Tester ▶️ January 5 - UX Design. First Free Lesson ▶️ January 9 - Sales Engineering. First Free Lesson Special offer for all participants! ️ ✅ Apply by the link https://crst.co/Dxfog 

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
An high level overview for becoming a machine learning engineer
An high level overview for becoming a machine learning engineer

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Practical MLops.pdf1.69 MB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
DATA CLEANING AND PROCESSING.pdf2.26 MB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Stats Notes 1.pdf4.06 MB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Cheatsheet Supervised Learning.pdf6.41 KB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
What topic does AI cover
What topic does AI cover

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Data Science Bookcamp Leonard Apeltsin, 2021

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Deep Learning from Scratch Seth Weidman, 2019

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
1. What do you understand by the term silhouette coefficient? The silhouette coefficient is a measure of how well clustered together a data point is with respect to the other points in its cluster. It is a measure of how similar a point is to the points in its own cluster, and how dissimilar it is to the points in other clusters. The silhouette coefficient ranges from -1 to 1, with 1 being the best possible score and -1 being the worst possible score. 2. What is the difference between trend and seasonality in time series? Trends and seasonality are two characteristics of time series metrics that break many models. Trends are continuous increases or decreases in a metric’s value. Seasonality, on the other hand, reflects periodic (cyclical) patterns that occur in a system, usually rising above a baseline and then decreasing again. 3. What is Bag of Words in NLP? Bag of Words is a commonly used model that depends on word frequencies or occurrences to train a classifier. This model creates an occurrence matrix for documents or sentences irrespective of its grammatical structure or word order. 4. What is the difference between bagging and boosting? Bagging is a homogeneous weak learners’ model that learns from each other independently in parallel and combines them for determining the model average. Boosting is also a homogeneous weak learners’ model but works differently from Bagging. In this model, learners learn sequentially and adaptively to improve model predictions of a learning algorithm ENJOY LEARNING 👍👍

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Hands on Plotly👍.pdf7.53 KB

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
Important metrics to monitor while monitoring machine learning model
Important metrics to monitor while monitoring machine learning model

Data Science & Machine Learning
Data Science & Machine Learningverified-telegram-icon
77 682
NumPy Bootcamp for Data Science and ML in Python - 2023 👇👇 https://t.me/udemy_free_courses_with_certi/1537 [Free for limited time only]