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 77 616 مشتركاً، محتلاً المرتبة 2 020 في فئة التعليم والمرتبة 3 811 في منطقة الهند.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 77 616 مشتركاً.
بحسب آخر البيانات بتاريخ 14 نوفمبر, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار -147، وفي آخر 24 ساعة بمقدار -20، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 2.41%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 0.97% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 1 872 مشاهدة. وخلال اليوم الأول يجمع عادةً 755 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 2.
- 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 15 نوفمبر, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التعليم.
77 616
المشتركون
-2024 ساعات
-947 أيام
-14730 أيام
أرشيف المشاركات
Which function is used to randomly reorder a Series or rows in Dataframe?
Which of the following is correct code to generate 20 normally distributed random numbers?
import numpy as np
Which type of data is separated into bins for analysis
Just a correction here
"np.nan" instead of "na.nan"
Hope you all are aware that mostly we
import numpy as np
Which of the following is incorrect code to replace na values with 0 in data?
Majority is correct
Well done guys 👍👍
Scikit learn can be specially used to solve classification, regression, clustering and dimensionality reduction problems
Which Scipy package can be used to solve differential equations?
Which Scipy package can be used for standard continuous and discrete probability distributions?
Some helpful Data science projects for beginners
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
https://www.kaggle.com/c/digit-recognizer
https://www.kaggle.com/c/titanic
BEST RESOURCES TO LEARN DATA SCIENCE AND MACHINE LEARNING FOR FREE
https://developers.google.com/machine-learning/crash-course
https://www.kaggle.com/learn/overview
https://forums.fast.ai/t/recommended-python-learning-resources/26888
https://www.fast.ai/
https://imp.i115008.net/JrBjZR
https://ern.li/OP/1qvkxbfaxqj
ENJOY LEARNING 👍👍
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🧑💻Programming and Hacking👩💻
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Python for Data Science
https://www.udemy.com/course/2021-learn-python-for-data-science-a-z-ver-59/?couponCode=PYTHON10
[Free for limited time only]
Which of the following is not a function of scikit learn?
An Artificial Neuron Network (ANN), popularly known as Neural Network is a computational model based on the structure and functions of biological neural networks. It is like an artificial human nervous system for receiving, processing, and transmitting information in terms of Computer Science.
Basically, there are 3 different layers in a neural network :
Input Layer (All the inputs are fed in the model through this layer)
Hidden Layers (There can be more than one hidden layers which are used for processing the inputs received from the input layers)
Output Layer (The data after processing is made available at the output layer)
Graph data can be used with a lot of learning tasks contain a lot rich relation data among elements. For example, modeling physics system, predicting protein interface, and classifying diseases require that a model learns from graph inputs. Graph reasoning models can also be used for learning from non-structural data like texts and images and reasoning on extracted structures.
Free Resources for Hacking and Programming
👇👇
https://t.me/joinchat/ZYXe60w7YisyNWEx
Top Bayesian Algorithms and Methods:
- Naive Bayes.
- Averages one-dependence estimators.
- Bayesian belief networks.
- Gaussian naive Bayes.
- Multinomial naive Bayes.
- Bayesian networks.
Data science Bootcamp with 5 projects
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https://www.udemy.com/course/data-science-bootcamp-with-python/?couponCode=FREE_UDS
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Some helpful Data science projects for beginners
https://www.kaggle.com/c/house-prices-advanced-regression-techniques
https://www.kaggle.com/c/digit-recognizer
https://www.kaggle.com/c/titanic
Intermediate Level Data science Projects
Black Friday Data : https://www.kaggle.com/sdolezel/black-friday
Human Activity Recognition Data : https://www.kaggle.com/uciml/human-activity-recognition-with-smartphones
Trip History Data : https://www.kaggle.com/pronto/cycle-share-dataset
Million Song Data : https://www.kaggle.com/c/msdchallenge
Census Income Data : https://www.kaggle.com/c/census-income/data
Movie Lens Data : https://www.kaggle.com/grouplens/movielens-20m-dataset
Twitter Classification Data : https://www.kaggle.com/c/twitter-sentiment-analysis2
Text mining : https://www.kaggle.com/kanncaa1/applying-text-mining
