Data Analytics
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Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making. Admin: @HusseinSheikho || @Hussein_Sheikho
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Red:📈 Análisis del canal de Telegram Data Analytics
El canal Data Analytics (@dataanalyticsx) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 29 838 suscriptores, ocupando la posición 4 345 en la categoría Tecnologías y Aplicaciones y el puesto 21 557 en la región Rusia.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 29 838 suscriptores.
Según los últimos datos del 26 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 302, y en las últimas 24 horas de -2, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 4.91%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.53% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 1 465 visualizaciones. En el primer día suele acumular 456 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 sellerflash, buybox, buyer, chaos, effortless.
📝 Descripción y política de contenido
El autor describe el recurso como un espacio para expresar opiniones subjetivas:
“Dive into the world of Data Analytics – uncover insights, explore trends, and master data-driven decision making.
Admin: @HusseinSheikho || @Hussein_Sheikho”
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 27 agosto, 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.
29 838
Suscriptores
-224 horas
+107 días
+30230 días
Archivo de publicaciones
29 838
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Repost from Machine Learning with Python
The guide Path to Senior Engineer Handbook has gathered resources for developers who want to advance to the level of Senior Engineer. 🚀
Inside: 📚
More than 50 newsletters on professional growth, system design, leadership, and web development. 📈
A selection of books on communication, technical writing, and building working relationships. 🤝
Selected YouTube channels, podcasts, and professional communities. 🎧
Courses, scientific articles, and educational platforms for a deeper study of topics. 🎓
A good starting point for those who want to improve not only their technical skills, but also their architectural thinking, communication, and leadership competencies. 💡
Link: https://github.com/jordan-cutler/path-to-senior-engineer-handbook?utm_source=opensourceprojects.dev&ref=opensourceprojects.dev
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Repost from Machine Learning with Python
🎓 A Free AI Course for Beginners by Microsoft
For those just getting into artificial intelligence, Microsoft offers a free course.
It runs for 12 weeks and includes 24 lessons with theory, hands-on assignments, labs, and quizzes.
The curriculum covers neural networks and deep learning, computer vision, natural language processing, genetic algorithms, and AI ethics. For practice, it uses the two main ML frameworks—TensorFlow and PyTorch.
Each lesson follows the same structure: first, reading material, then a Jupyter notebook with code, and for some topics, a lab. The course is in English but has been translated into dozens of languages.
➡️ All materials and links are on GitHub
https://github.com/microsoft/AI-For-Beginners/blob/main/translations/ru/README.md
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Repost from Machine Learning with Python
10 GitHub repositories that are worth checking out for an AI engineer 🤖
1. Hands-On AI Engineering 🛠️
A collection of AI applications and agent systems with practical use cases of LLM.
👉 https://github.com/Sumanth077/Hands-On-AI-Engineering
2. Hands-On Large Language Models 📘
Full code from the book Hands-On Large Language Models: from basics to fine-tuning.
👉 https://github.com/HandsOnLLM/Hands-On-Large-Language-Models
3. AI Agents for Beginners 🎓
A free course from Microsoft with 11 lessons on creating AI agents.
👉 https://github.com/microsoft/ai-agents-for-beginners
4. GenAI Agents 🤖
A large collection of tutorials and implementations of agent systems.
👉 https://github.com/NirDiamant/GenAI_Agents
5. Made With ML 🚀
About the development, deployment, and support of production-ready ML systems.
👉 https://github.com/GokuMohandas/Made-With-ML
6. Learn Harness Engineering ⚙️
A practical course on Harness Engineering for AI agents.
👉 https://github.com/walkinglabs/learn-harness-engineering
7. AutoResearch 🔬
Autonomous cycles of ML experiments from Andrej Karpathy.
👉 https://github.com/karpathy/autoresearch
8. Designing Machine Learning Systems 📚
Notes and materials from Chip Huyen's book.
👉 https://github.com/chiphuyen/dmls-book
9. Awesome LLM Inference ⚡
A collection of materials on LLM inference: Flash Attention, KV Cache, quantization, and more.
👉 https://github.com/xlite-dev/Awesome-LLM-Inference
10. LLM Course 🗺️
A practical course on LLM with a roadmap and Colab notebooks.
👉 https://github.com/mlabonne/llm-course
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