¡No caigas en manos de tramposos! Telemetrio encuentra y marca estos canales 👉 Si quieres ver la etiqueta, suscríbete

Artificial Intelligence

Ir al canal en Telegram

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

Red:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert India5 954 Educación3 067...

📈 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 56 610 suscriptores, ocupando la posición 3 067 en la categoría Educación y el puesto 5 954 en la región India.

📊 Métricas de audiencia y dinámica

Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 56 610 suscriptores.

Según los últimos datos del 31 octubre, 2026, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de 437, y en las últimas 24 horas de 3, conservando un alto alcance.

Estado de verificación: No verificado
Tasa de interacción (ER): El promedio de interacción de la audiencia es 4.10%. Durante las primeras 24 horas tras publicar, el contenido suele obtener 1.54% de reacciones respecto al total de suscriptores.
Alcance de las publicaciones: Cada publicación recibe en promedio 2 323 visualizaciones. En el primer día suele acumular 874 visualizaciones.
Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 12.
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 01 noviembre, 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.

56 610

Suscriptores

+324 horas

+647 días

+43730 días

2 323

Visitas de la publicación

~ 87424 horas

~ 1 02448 horas

4.10%

Tasa de compromiso

Sin datos

Mensajes por día

Ads index

beta

Archivo de publicaciones

56 610

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

56 610

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.

56 610

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.

56 610

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.

56 610

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.

56 610

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]

56 610

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

56 610

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.

56 610

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.

56 610

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.

56 610

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

56 610

#meme

56 610

Data Science Essentials in Python.pdf5.01 MB

56 610

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"

56 610

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.

56 610

6. Implement the LLM call function. • Asynchronously calls the LLM with the user's prompt • Returns the model name and its response

56 610

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

56 610

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

56 610

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