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Best Channel for Programmers and Hackers All in one channel to learn 👇 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun

Red:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert India13 566 Educación6 252...

📈 Análisis del canal de Telegram Coding Free Books | Python | AI

El canal Coding Free Books | Python | AI (@codingwithsagar) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 30 887 suscriptores, ocupando la posición 6 252 en la categoría Educación y el puesto 13 566 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 30 887 suscriptores.

Según los últimos datos del 21 junio, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 148, y en las últimas 24 horas de 0, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 3.76%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 1 161 visualizaciones. En el primer día suele acumular 0 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 4.
Intereses temáticos: El contenido se centra en temas clave como learning, link:-, css, algorithm, sql.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Best Channel for Programmers and Hackers All in one channel to learn 👇 1. Python 2. Ethical Hacking 3. Java 4. App development 5. Machine learning 6. Data structures 7. Algorithms Promotions: @coderfun”

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 22 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 Educación.

30 887

Suscriptores

Sin datos24 horas

-127 días

+14830 días

1 161

Visitas de la publicación

Sin datos24 horas

Sin datos48 horas

3.76%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

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𝐒𝐭𝐚𝐜𝐤 𝐃𝐚𝐭𝐚 𝐒𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞 𝐢𝐧 𝐏𝐲𝐭𝐡𝐨𝐧

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Refactoring Analytics Models Sooner or later, every data professional faces the need to refactor analytical models. For example, you might need to migrate SQL models from Airflow to dbt, or overhaul a dbt project for scalability and best practices. While every refactoring project is unique, there are some common rules that can help guide the process. Here are 6 guidelines to help you succeed. 🔹 Rule 1. Don't break production analytics Make sure that production reports and systems are not affected. Refactoring is the full responsibility of engineers and analysts. 🔹 Rule 2. Define new rules Define conventions that satisfy your team, like modeling layers, naming rules, etc. 🔹 Rule 3. Inspect existing models It helps in creating a refactoring plan: - Some models may be easy to migrate (loosely coupled) - Some models will require additional work 🔹 Rule 4. Start from the end Knowing the end goal will help you decide which data sources and intermediates are required for the final table. 🔹 Rule 5. Proceed in small chunks Proceed in small increments. Deliver small, yet complete, changes that are easy to review and deploy. 🔹 Rule 6. Beginning is hard, but it gets easier At the start of the migration, you will face a lot of work: every new model will be implemented from scratch and require significant groundwork. However, the more you do at the beginning, the easier it will be in the end. #sql #dbt #dataanalytics

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R language complete notes 🎶

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DSA .pdf16.95 MB

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Grokking Algorithms In Python.pdf6.19 MB

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Bio-inspired Algorithms in Machine Learning and Deep Learnin.pdf3.49 MB

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🔅 Python Function

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RNotesForProfessionals.pdf6.47 MB

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Raspberry Pi for Beginners Papercut, 18th ed, 2024

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Linux_ The_Ultimate_Guide.pdf4.72 MB

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