Machine Learning
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
إظهار المزيد📈 نظرة تحليلية على قناة تيليجرام Machine Learning
تُعد قناة Machine Learning (@machinelearning9) في القطاع اللغوي الإنكليزية لاعباً نشطاً. يضم المجتمع حالياً 40 106 مشتركاً، محتلاً المرتبة 3 384 في فئة التكنولوجيات والتطبيقات والمرتبة 231 في منطقة سوريا.
📊 مؤشرات الجمهور والحراك
منذ تأسيسه في невідомо، حقق المشروع نمواً سريعاً وجمع 40 106 مشتركاً.
بحسب آخر البيانات بتاريخ 24 يونيو, 2026، تحافظ القناة على نشاط مستقر. خلال آخر 30 يوماً تغيّر عدد الأعضاء بمقدار 401، وفي آخر 24 ساعة بمقدار 38، مع بقاء الوصول العام مرتفعاً.
- حالة التحقق: غير موثّقة
- معدل التفاعل (ER): يبلغ متوسط تفاعل الجمهور 1.96%. وخلال أول 24 ساعة من النشر يحصد المحتوى عادةً 1.16% من ردود الفعل نسبةً إلى إجمالي المشتركين.
- وصول المنشورات: يحصل كل منشور على متوسط 788 مشاهدة. وخلال اليوم الأول يجمع عادةً 465 مشاهدة.
- التفاعلات والاستجابة: يتفاعل الجمهور بانتظام؛ متوسط التفاعلات لكل منشور يبلغ 2.
- الاهتمامات الموضوعية: يركز المحتوى على مواضيع رئيسية مثل distance, insidead, gpu, learning, degree.
📝 الوصف وسياسة المحتوى
يصف المؤلف القناة بأنها مساحة للتعبير عن الآراء الذاتية:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
بفضل وتيرة التحديث المرتفعة (أحدث البيانات بتاريخ 25 يونيو, 2026) تحافظ القناة على حداثتها ومستوى وصول مرتفع. وتُظهر التحليلات تفاعلاً نشطاً من الجمهور، ما يجعلها نقطة تأثير مهمة ضمن فئة التكنولوجيات والتطبيقات.
جاري تحميل البيانات...
| التاريخ | نمو المشتركين | الإشارات | القنوات | |
| 25 يونيو | +1 | |||
| 24 يونيو | +38 | |||
| 23 يونيو | +34 | |||
| 22 يونيو | +9 | |||
| 21 يونيو | +10 | |||
| 20 يونيو | +10 | |||
| 19 يونيو | +8 | |||
| 18 يونيو | +13 | |||
| 17 يونيو | +17 | |||
| 16 يونيو | +23 | |||
| 15 يونيو | +33 | |||
| 14 يونيو | +24 | |||
| 13 يونيو | +14 | |||
| 12 يونيو | +27 | |||
| 11 يونيو | +12 | |||
| 10 يونيو | +20 | |||
| 09 يونيو | +8 | |||
| 08 يونيو | +14 | |||
| 07 يونيو | +18 | |||
| 06 يونيو | +17 | |||
| 05 يونيو | +24 | |||
| 04 يونيو | +24 | |||
| 03 يونيو | +26 | |||
| 02 يونيو | +33 | |||
| 01 يونيو | +31 |
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| 6 | PANDAS — CHEAT SHEET
1. DATA LOADING
Method | What it does
----------------+--------------------
pd.read_csv() | Reads CSV file
pd.read_excel() | Reads Excel file
pd.read_sql() | Reads data from SQL
pd.read_json() | Reads JSON file
2. DATA ANALYSIS
Method | What it does
--------------+---------------------------
df.head() | Shows first rows
df.info() | Table information
df.describe() | Statistics by columns
df.shape | Table size (rows, columns)
df.columns | List of column names
3. DATA SELECTION
Method | What it does
-----------+----------------------------------
df.loc[] | Selection by row and column names
df.iloc[] | Selection by indices
df.query() | Filtering by condition
4. DATA CLEANING
Method | What it does
---------------------+--------------------------------
df.isnull() | Check for missing values (NULL)
df.dropna() | Remove rows with missing values
df.fillna() | Fill missing values
df.drop_duplicates() | Remove duplicates
df.astype() | Change data type
5. ANALYTICS
Method | What it does
------------------+----------------------------
df.groupby() | Data grouping
df.agg() | Aggregation in groups
df.value_counts() | Count of unique values
df.mean() | Mean value
df.median() | Median
df.corr() | Correlation between columns
6. DATA MERGING
Method | What it does
------------+---------------------
pd.merge() | SQL JOIN by column
pd.join() | JOIN by index
pd.concat() | Glue tables together
⭐ TOP 10 METHODS
read_csv() head() info() loc[] iloc[] query() groupby() merge() fillna() sort_values() | 673 |
| 7 | PANDAS — CHEAT SHEET
1. DATA LOADING
Method | What it does
----------------+--------------------
pd.read_csv() | Reads CSV file
pd.read_excel() | Reads Excel file
pd.read_sql() | Reads data from SQL
pd.read_json() | Reads JSON file
2. DATA ANALYSIS
Method | What it does
--------------+---------------------------
df.head() | Shows first rows
df.info() | Table information
df.describe() | Statistics by columns
df.shape | Table size (rows, columns)
df.columns | List of column names
3. DATA SELECTION
Method | What it does
-----------+----------------------------------
df.loc[] | Selection by row and column names
df.iloc[] | Selection by indices
df.query() | Filtering by condition
4. DATA CLEANING
Method | What it does
---------------------+--------------------------------
df.isnull() | Check for missing values (NULL)
df.dropna() | Remove rows with missing values
df.fillna() | Fill missing values
df.drop_duplicates() | Remove duplicates
df.astype() | Change data type
5. ANALYTICS
Method | What it does
------------------+----------------------------
df.groupby() | Data grouping
df.agg() | Aggregation in groups
df.value_counts() | Count of unique values
df.mean() | Mean value
df.median() | Median
df.corr() | Correlation between columns
6. DATA MERGING
Method | What it does
------------+---------------------
pd.merge() | SQL JOIN by column
pd.join() | JOIN by index
pd.concat() | Glue tables together
⭐ TOP 10 METHODS
read_csv() head() info() loc[] iloc[] query() groupby() merge() fillna() sort_values() | 1 |
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| 12 | My favorite way to work with multiple filters in pandas.Series — not a chain of .loc, but a single mask. 🐼
The chain looks neat, but breaks on real data and easily gives unexpected results:
s = pd.Series([10, 15, 20, 25, 30])
s.loc[s > 20].loc[s % 2 == 1]
The problem is that the second .loc again looks at the original s, not the already filtered result. The logic gets messy. 🤯
It's more reliable to gather everything into one expression:
s = pd.Series([10, 15, 20, 25, 30])
mask = (s > 20) & (s % 2 == 1)
result = s.loc[mask]
One mask, one point of truth. ✅
It's easier to debug. Fewer surprises when the code grows. 🚀
#Pandas #Python #DataScience #CodingTips #DataEngineering #Debugging
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| 14 | A free MIT guide to key computer vision concepts 📘
Link: https://visionbook.mit.edu/ 🔗
#ComputerVision #MIT #AI #MachineLearning #Tech #DataScience
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| 15 | Learn AI for free directly from top companies. 🚀
1 - Anthropic:
anthropic.skilljar.com
2 - Google:
grow.google/ai
3 - Meta:
ai.meta.com/resources/
4 - NVIDIA:
developer.nvidia.com/cuda
5 - Microsoft:
learn.microsoft.com/en-us/training/
6 - OpenAI:
academy.openai.com
7 - IBM:
skillsbuild.org
8 - AWS:
skillbuilder.aws
9 - DeepLearning.AI:
deeplearning.ai
10 - Hugging Face:
huggingface.co/learn
💬 Comment "Learning" if you find this helpful.
🔄 Repost so others can take help.
🔖 Must bookmark for future reference.
#AI #MachineLearning #Tech #FreeLearning #DataScience #AIForAll
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متاح الآن! بحث تيليغرام 2025 — أهم رؤى العام 
