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Artificial Intelligence

Artificial Intelligence

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🔰 Machine Learning & Artificial Intelligence Free Resources 🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more For Promotions: @love_data

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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
Gradient_descent.pdf2.00 KB

Artificial Intelligence Market Size
Artificial Intelligence Market Size

How to master ChatGPT-4o.... The secret? Prompt engineering. These 9 frameworks will help you! APE ↳ Action, Purpose, Expectation Action: Define the job or activity. Purpose: Discuss the goal. Expectation: State the desired outcome. RACE ↳ Role, Action, Context, Expectation Role: Specify ChatGPT's role. Action: Detail the necessary action. Context: Provide situational details. Expectation: Describe the expected outcome. COAST ↳ Context, Objective, Actions, Scenario, Task Context: Set the stage. Objective: Describe the goal. Actions: Explain needed steps. Scenario: Describe the situation. Task: Outline the task. TAG ↳ Task, Action, Goal Task: Define the task. Action: Describe the steps. Goal: Explain the end goal. RISE ↳ Role, Input, Steps, Expectation Role: Specify ChatGPT's role. Input: Provide necessary information. Steps: Detail the steps. Expectation: Describe the result. TRACE ↳ Task, Request, Action, Context, Example Task: Define the task. Request: Describe the need. Action: State the required action. Context: Provide the situation. Example: Illustrate with an example. ERA ↳ Expectation, Role, Action Expectation: Describe the desired result. Role: Specify ChatGPT's role. Action: Specify needed actions. CARE ↳ Context, Action, Result, Example Context: Set the stage. Action: Describe the task. Result: Describe the outcome. Example: Give an illustration. ROSES ↳ Role, Objective, Scenario, Expected Solution, Steps Role: Specify ChatGPT's role. Objective: State the goal or aim. Scenario: Describe the situation. Expected Solution: Define the outcome. Steps: Ask for necessary actions to reach solution. Join for more: https://t.me/machinelearning_deeplearning

Andrew Ng's course on ChatGPT Prompt Engineering for Developers, created together with OpenAI, is available now for free! 👇👇 https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/

10. Explaining Career Transitions: How can I effectively explain a career transition to [JOB TITLE] in [SPECIFIC INDUSTRY] during an interview? Given my background in [previous industry or role] and my recent [relevant education, certification, experience], provide a narrative that connects my previous experiences to the new role, highlighting transferable skills and relevant achievements. ChatGPT PROMPTS Series

9. Dealing with Gaps in Employment: How should I address gaps in my employment history during an interview for the [JOB TITLE] position in [SPECIFIC INDUSTRY]? Considering that during this period I [explain what you did: pursued education, volunteered, freelanced, etc.], provide a response that explains the gaps positively and focuses on what I’ve learned during that time.

8. Handling Behavioral Questions: How can I best respond to behavioral interview questions for a [JOB TITLE] role? Given my experience in [specific past role or project], provide strategies and examples to answer questions about teamwork, conflict resolution, and leadership.

7. Dealing with Gaps in Employment: What is the best way to follow up after an interview for the [JOB TITLE] role at [SPECIFIC COMPANY]? Considering our discussion on [specific topics discussed during the interview], craft a professional and thoughtful thank-you email that reiterates my interest, highlights key points from our conversation, and emphasizes how my background in [specific skills or experiences] aligns with the company’s needs.

6. Showcasing Soft Skills: How can I effectively highlight my soft skills, such as communication and teamwork, during an interview for the [JOB TITLE] role in [SPECIFIC INDUSTRY]? Please provide examples and scenarios that demonstrate these skills in action.

5. Post-Interview Follow-Up: What is the best way to follow up after an interview for the [JOB TITLE] role at [SPECIFIC COMPANY]? Based on our discussion about [specific project, skill, or topic discussed during the interview], draft a professional and personalized thank-you email that not only reiterates my enthusiasm for the role but also highlights how my experience in [specific relevant experience or achievement] can directly contribute to the success of [SPECIFIC COMPANY]

4. Negotiating Salary: How should I approach salary negotiations for a [JOB TITLE] role at [SPECIFIC COMPANY]? Please provide a script or key points to emphasize based on industry standards and my qualifications. ChatGPT PROMPTS Series

3. Overcoming Weaknesses: How should I address the common interview question: 'What is your greatest weakness?' in the context of a [JOB TITLE] role in [SPECIFIC INDUSTRY]? Provide a response that turns the weakness into a positive aspect.

2. Mock Interview Practice: Create a mock interview scenario for the [JOB TITLE] role at [SPECIFIC COMPANY]. Include 5 common and challenging questions I might face, and provide guidance on how to answer each effectively.

1. Developing STAR Method Responses: Help me craft a STAR (Situation, Task, Action, Result) response to the interview question: [INSERT QUESTION] for the [JOB TITLE] role. Ensure the response is clear, concise, and demonstrates my impact in previous roles.

Here are 10 ChatGPT-4o Prompts you need to know to Dominate and Excel at any job interview:

#meme
#meme

Data Science Essentials in Python.pdf5.01 MB

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8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the
8. Set up the user interface and trigger the main function. • Provides an input field for the user's question • Triggers the main function when the user clicks "Get Answer"

7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays indi
7. Define the main function to run all LLMs and aggregate results. • Runs all reference models asynchronously • Displays individual responses in expandable sections • Aggregates responses using the aggregator model • Streams the aggregated response.