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Artificial Intelligence

Artificial Intelligence

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📈 Análisis del canal de Telegram Artificial Intelligence

El canal Artificial Intelligence (@machinelearning_deeplearning) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 55 402 suscriptores, ocupando la posición 3 050 en la categoría Educación y el puesto 6 211 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 55 402 suscriptores.

Según los últimos datos del 30 agosto, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 683, y en las últimas 24 horas de 41, conservando un alto alcance.

  • Estado de verificación: No verificado
  • Tasa de interacción (ER): El promedio de interacción de la audiencia es 5.87%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.33% de reacciones respecto al total de suscriptores.
  • Alcance de las publicaciones: Cada publicación recibe en promedio 3 250 visualizaciones. En el primer día suele acumular 736 visualizaciones.
  • Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 25.
  • Intereses temáticos: El contenido se centra en temas clave como learning, classification, layer, pattern, chatbot.

📝 Descripción y política de contenido

El autor describe el recurso como un espacio para expresar opiniones subjetivas:
🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data

Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 31 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 Educación.

55 402
Suscriptores
+4124 horas
+1517 días
+68330 días
Archivo de publicaciones
6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its re
6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its response

5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the agg
5. Define the models and aggregator system prompt. • Specifies the LLMs to be used for generating responses • Defines the aggregator model and its system prompt

4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and a
4. Initialize Together AI clients. • Sets up Together API key as an environment variable • Initializes both synchronous and asynchronous Together clients

3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API
3. Set up the Streamlit app and API key input. • Creates a title for the app • Adds a secure input field for the Together API key

2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM i
2. Import necessary libraries • Streamlit for the web interface • asyncio for asynchronous operations • Together AI for LLM interactions

1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:
1. Install the necessary Python Libraries Run the following commands from your terminal to install the required libraries:

Build an LLM app with Mixture of AI Agents using small Open Source LLMs that can beat GPT-4o in just 40 lines of Python Code (step-by-step instructions): ⬇️

You can use ChatGPT to make money online. Here are 10 prompts by ChatGPT 1. Develop Email Newsletters: Make interesting email
You can use ChatGPT to make money online. Here are 10 prompts by ChatGPT 1. Develop Email Newsletters: Make interesting email newsletters to keep audience updated and engaged. Prompt: "I run a local community news website. Can you help me create a weekly email newsletter that highlights key local events, stories, and updates in a compelling way?" 2. Create Online Course Material: Make detailed and educational online course content. Prompt: "I'm creating an online course about basic programming for beginners. Can you help me generate a syllabus and detailed lesson plans that cover fundamental concepts in an easy-to-understand manner?" Read more......

Machine_Learning_in_Finance_From_Theory_to_Practice_Matthew_F_Dixon.pdf8.75 MB

Free ML crash course by Google 👇👇 https://developers.google.com/machine-learning/crash-course/

Matrix Theory and Linear Algebra Peter Selinger, 2018

Here's a simple but powerful test to see the intelligence of an AI model. (The answer is the strawberry is still on the table) Go ahead and ask any model this: Assume the laws of physics on Earth. A small strawberry is put into a normal cup and the cup is placed upside down on a table. Someone then takes the cup and puts it inside the microwave. Where is the strawberry now? Explain your reasoning step by step.

AI as a life saver: 1. ChatGPT - thesis, essay, writing 2. Scite and perplexity - literature review 3. Consesus - latest research paper 4. Gemini - coding and technical 5. Claude AI - Analysis data, comparison data, literature review

DeepLearning Notes

ChatGPT is a profit powerhouse for designers. 10 ChatGPT / ClaudeAI prompts that help you make 6000$ / month. ( Start selling in 7 days or less ) ⬇👇 ChatGPT Prompt Master

Modern Deep Learning for Tabular Data Andre Ye, 2023

Fundamentals of Deep Learning Nithin Buduma, 2022

Machine Learning short notes.pdf5.34 MB

Artificial Intelligence, Game Theory and Mechanism Design in Politics Tshilidzi Marwala, 2023