¡Ya disponible! Investigación de Telegram 2025 — los principales insights del año 
Machine Learning
Ir al canal en Telegram
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
Mostrar más📈 Análisis del canal de Telegram Machine Learning
El canal Machine Learning (@machinelearning9) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 40 106 suscriptores, ocupando la posición 3 384 en la categoría Tecnologías y Aplicaciones y el puesto 231 en la región Siria.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 40 106 suscriptores.
Según los últimos datos del 24 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 401, y en las últimas 24 horas de 38, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 1.96%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.16% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 788 visualizaciones. En el primer día suele acumular 465 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 2.
- Intereses temáticos: El contenido se centra en temas clave como distance, insidead, gpu, learning, degree.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 25 junio, 2026), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Tecnologías y Aplicaciones.
40 106
Suscriptores
+3824 horas
+637 días
+40130 días
Carga de datos en curso...
Canales Similares
Nube de Etiquetas
Menciones Entrantes y Salientes
---
---
---
---
---
---
Atraer Suscriptores
junio '26
junio '26
+488
en 4 canales
mayo '26
+748
en 10 canales
Get PRO
abril '26
+423
en 8 canales
Get PRO
marzo '26
+286
en 7 canales
Get PRO
febrero '26
+467
en 12 canales
Get PRO
enero '26
+624
en 13 canales
Get PRO
diciembre '25
+678
en 14 canales
Get PRO
noviembre '25
+642
en 3 canales
Get PRO
octubre '25
+1 052
en 9 canales
Get PRO
septiembre '25
+1 012
en 8 canales
Get PRO
agosto '25
+470
en 3 canales
Get PRO
julio '25
+1 113
en 14 canales
Get PRO
junio '25
+876
en 5 canales
Get PRO
mayo '25
+1 030
en 2 canales
Get PRO
abril '25
+1 368
en 2 canales
Get PRO
marzo '25
+820
en 1 canales
Get PRO
febrero '25
+1 068
en 6 canales
Get PRO
enero '25
+1 062
en 4 canales
Get PRO
diciembre '24
+895
en 4 canales
Get PRO
noviembre '24
+1 359
en 14 canales
Get PRO
octubre '24
+1 841
en 14 canales
Get PRO
septiembre '24
+1 406
en 16 canales
Get PRO
agosto '24
+1 739
en 13 canales
Get PRO
julio '24
+1 108
en 14 canales
Get PRO
junio '24
+1 335
en 12 canales
Get PRO
mayo '24
+1 257
en 15 canales
Get PRO
abril '24
+1 349
en 7 canales
Get PRO
marzo '24
+1 778
en 11 canales
Get PRO
febrero '24
+1 882
en 12 canales
Get PRO
enero '24
+2 482
en 16 canales
Get PRO
diciembre '23
+1 638
en 17 canales
Get PRO
noviembre '23
+1 420
en 14 canales
Get PRO
octubre '23
+811
en 15 canales
Get PRO
septiembre '23
+1 076
en 0 canales
Get PRO
agosto '23
+1 246
en 0 canales
Get PRO
julio '23
+4 094
en 0 canales
Get PRO
junio '23
+1 831
en 0 canales
Get PRO
mayo '23
+1 304
en 0 canales
| Fecha | Crecimiento de Suscriptores | Menciones | Canales | |
| 25 junio | +1 | |||
| 24 junio | +38 | |||
| 23 junio | +34 | |||
| 22 junio | +9 | |||
| 21 junio | +10 | |||
| 20 junio | +10 | |||
| 19 junio | +8 | |||
| 18 junio | +13 | |||
| 17 junio | +17 | |||
| 16 junio | +23 | |||
| 15 junio | +33 | |||
| 14 junio | +24 | |||
| 13 junio | +14 | |||
| 12 junio | +27 | |||
| 11 junio | +12 | |||
| 10 junio | +20 | |||
| 09 junio | +8 | |||
| 08 junio | +14 | |||
| 07 junio | +18 | |||
| 06 junio | +17 | |||
| 05 junio | +24 | |||
| 04 junio | +24 | |||
| 03 junio | +26 | |||
| 02 junio | +33 | |||
| 01 junio | +31 |
Publicaciones del Canal
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
| 2 | 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 | 35 |
| 3 | Sin texto... | 299 |
| 4 | 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 | 29 |
| 5 | 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 | 1 |
| 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 |
| 8 | 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 | 26 |
| 9 | 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 | 43 |
| 10 |  Sin texto... | 838 |
| 11 | 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 | 115 |
| 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
✨ 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 | 794 |
| 13 | 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 | 136 |
| 14 |  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 | 913 |
| 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
https://t.me/CodeProgrammer | 627 |
| 16 | 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 | 73 |
| 17 | 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 | 73 |
| 18 | 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 | 1 |
| 19 | 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 | 1 |
| 20 | Maczo Pet Monster Game
AF 80%
Join 👉👉 @maczopet_bot | 462 |
