Machine Learning

前往频道在 Telegram

Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho

显示更多

网络:Machine Learning with Python 叙利亚232 技术与应用3 398...

📈 Telegram 频道 Machine Learning 的分析概览

频道 Machine Learning (@machinelearning9) 英语语言赛道中的是活跃参与者。目前社区聚集了 40 072 名订阅者，在 技术与应用 类别中位列第 3 398，并在 叙利亚 地区排名第 232 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 40 072 名订阅者。

根据 23 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 379，过去 24 小时变化为 30，整体触达仍然可观。

认证状态： 未认证
互动率 (ER)： 平均受众互动率为 1.92%。内容发布后 24 小时内通常能获得 1.16% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 770 次浏览，首日通常累积 466 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 3。
主题关注点： 内容集中在 distance, insidead, gpu, learning, degree 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho”

凭借高频更新（最新数据采集于 24 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。

40 072

订阅者

+3024 小时

+337 天

+37930 天

770

帖子浏览量

~ 46624 小时

~ 62048 小时

1.92%

参与率

~ 3

每日帖子数

Ads index

beta

帖子存档

40 087

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()

40 087

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()

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

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 ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

A free MIT guide to key computer vision concepts 📘 Link: https://visionbook.mit.edu/ 🔗 #ComputerVision #MIT #AI #MachineLearning #Tech #DataScience ✨ Join Best TG Channels https://t.me/addlist/0f6vfFbEMdAwODBk ⭐️ Join Our WhatsApp Channel https://whatsapp.com/channel/0029VaC7Weq29753hpcggW2A 🚀 Level up your AI & Data Science skills with HelloEncyclo — a growing all-in-one platform featuring hands-on courses in LLMs, Deep Learning, MLOps, Data Engineering, and more. ✅ 13 courses live + 40+ coming soon 🎯 One access, lifetime updates 🔑 Use code: PRESALE-BOOK-WAVE-2GFG 👉 https://helloencyclo.com/?ref=HUSSEINSHEIKHO

40 087

Repost from Machine Learning with Python

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 https://t.me/CodeProgrammer

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

Maczo Pet Monster Game AF 80% Join 👉👉 @maczopet_bot

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds

40 087

New to LBank? Unlock VIP2 and Trading Rewards VIP2 trial, transfer rewards, and trading bonuses for new users. Offer available until June 30. Sponsored By WaybienAds