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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
Show more📈 Analytical overview of Telegram channel Artificial Intelligence
Channel Artificial Intelligence (@machinelearning_deeplearning) in the English language segment is an active participant. Currently, the community unites 53 195 subscribers, ranking 3 254 in the Education category and 7 029 in the India region.
📊 Audience metrics and dynamics
Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 53 195 subscribers.
According to the latest data from 10 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 1 050 over the last 30 days and by 35 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 5.80%. Within the first 24 hours after publication, content typically collects 1.68% reactions from the total number of subscribers.
- Post reach: On average, each post receives 3 086 views. Within the first day, a publication typically gains 892 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 9.
- Thematic interests: Content is focused on key topics such as learning, classification, layer, pattern, chatbot.
📝 Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
“🔰 Machine Learning & Artificial Intelligence Free Resources
🔰 Learn Data Science, Deep Learning, Python with Tensorflow, Keras & many more
For Promotions: @love_data”
Thanks to the high frequency of updates (latest data received on 11 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
53 195
Subscribers
+3524 hours
+1927 days
+1 05030 days
Posts Archive
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CHAT GPT PROMPTS TO HELP YOU FIND A JOB FAST 🚀
1. Tailored Resume Optimizer Prompt:
Analyze my resume and this job description for [Dream Job Title]. Suggest 5 specific modifications to align my resume perfectly with the job requirements. Present changes in a before/after format with explanations. Here's my resume: [Paste Resume]. Here's the job description: [Paste Job Description]
ChatGPT PROMPTS
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Whilst we are on this reflection topic. Damn good system prompt for anyone who is using an LLM API or just a good prompt
You are an AI assistant designed to provide detailed, step-by-step responses. Your outputs should follow this structure:
1. Begin with a <thinking> section.
2. Inside the thinking section:
a. Briefly analyze the question and outline your approach.
b. Present a clear plan of steps to solve the problem.
c. Use a "Chain of Thought" reasoning process if necessary, breaking down your thought process into numbered steps.
3. Include a <reflection> section for each idea where you:
a. Review your reasoning.
b. Check for potential errors or oversights.
c. Confirm or adjust your conclusion if necessary.
4. Be sure to close all reflection sections.
5. Close the thinking section with </thinking>.
6. Provide your final answer in an <output> section.
Always use these tags in your responses. Be thorough in your explanations, showing each step of your reasoning process. Aim to be precise and logical in your approach, and don't hesitate to break down complex problems into simpler components. Your tone should be analytical and slightly formal, focusing on clear communication of your thought process.
Remember: Both <thinking> and <reflection> MUST be tags and must be closed at their conclusion
Make sure all <tags> are on separate lines with no other text. Do not include other text on a line containing a tag.53 207
Do these 4 things to 10x your responses while asking for referrals:
1. Be personal. (never use AI)
I get a ton of messages that are either written by AI or obviously copy and pasted to 100 people.
Be personal by mentioning something you have in common with the person you’re messaging or what you got out of one of their posts.
2. Have a specific job that you want to apply for and send the link.
“Can you look and see if there are any openings?” is incredibly rude and inconsiderate of the person’s time.
If you want them to help you with a referral, do the work for them by sending them the link, why you’re a good fit, and other needed info.
3. Reach out to people who are active on LinkedIn, but not content creators.
Everytime there’s an opening at my company, I get 50 messages asking for a referral. As much as I want to, I can’t refer everyone.
Therefore, look for those to connect with at a company you’re interested in that post occasionally on LinkedIn, but are not content creators.
These people will be active enough to see your message, but not have 3 dozen other messages asking for the same thing.
4. Build relationships way before you ask for a referral.
While I don’t do many referrals bc of how many inquiries I get, I’d be much more likely to refer someone who adds to the conversation by commenting on my posts, creates good posts themselves, and overall seems like a smart, nice person.
Doing this turns you from a complete stranger to a friend.
I know a lot of people are pressed for time on here, but building relationships is what networking is all about.
Do that effectively and your network may offer you referrals when there’s an opening.
Join this channel for more Interview Preparation Tips: https://t.me/jobinterviewsprep
ENJOY LEARNING 👍👍
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Advanced AI and Data Science Interview Questions
1. Explain the concept of Generative Adversarial Networks (GANs). How do they work, and what are some of their applications?
2. What is the Curse of Dimensionality? How does it affect machine learning models, and what techniques can be used to mitigate its impact?
3. Describe the process of hyperparameter tuning in deep learning. What are some strategies you can use to optimize hyperparameters?
4. How does a Transformer architecture differ from traditional RNNs and LSTMs? Why has it become so popular in natural language processing (NLP)?
5. What is the difference between L1 and L2 regularization, and in what scenarios would you prefer one over the other?
6. Explain the concept of transfer learning. How can pre-trained models be used in a new but related task?
7. Discuss the importance of explainability in AI models. How do methods like LIME or SHAP contribute to model interpretability?
8. What are the differences between Reinforcement Learning (RL) and Supervised Learning? Can you provide an example where RL would be more appropriate?
9. How do you handle imbalanced datasets in a classification problem? Discuss techniques like SMOTE, ADASYN, or cost-sensitive learning.
10. What is Bayesian Optimization, and how does it compare to grid search or random search for hyperparameter tuning?
11. Describe the steps involved in developing a recommendation system. What algorithms might you use, and how would you evaluate its performance?
12. Can you explain the concept of autoencoders? How are they used for tasks such as dimensionality reduction or anomaly detection?
13. What are adversarial examples in the context of machine learning models? How can they be used to fool models, and what can be done to defend against them?
14. Discuss the role of attention mechanisms in neural networks. How have they improved performance in tasks like machine translation?
15. What is a variational autoencoder (VAE)? How does it differ from a standard autoencoder, and what are its benefits in generating new data?
I have curated the best interview resources to crack Data Science Interviews
👇👇
https://topmate.io/analyst/1024129
Like if you need similar content 😄👍
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Job hunting? Your resume is your first impression—make it count!
Don’t just list what you did or your responsibilities; showcase the impact you made.
❌ “Developed a ML model to predict customer churn.”
✅ “Built a churn prediction model using logistic regression, reducing churn by 12% and retaining $2M in quarterly revenue.”
See the difference? One’s a task; the other’s a success. Employers want to see the value you bring, not just the work you’ve done.
You would have heard the saying, “A single sheet of paper can’t decide my future,” but this single page can.😉
Remember, your resume isn’t just a record—it’s your professional life in a single page.
I have curated the best resources to learn Data Science & Machine Learning
👇👇
https://topmate.io/coding/914624
All the best 👍👍
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Machine learning engineers shouldn't only grow through years of hard work.
Learning this way is too slow and complacent.
You can grow much faster by actively:
- Collaborating with talented professionals
- Finding a mentor who is 2-5 years ahead
- Taking on ambitious projects outside of your comfort zone
Hard work can only take you so far, meanwhile leveraging a network and daring to take on challenges will 10x your growth.
I have curated the best interview resources to crack Data Science Interviews
👇👇
https://topmate.io/analyst/1024129
Like if you need similar content 😄👍
53 207
Machine learning engineers shouldn't only grow through years of hard work.
Learning this way is too slow and complacent.
You can grow much faster by actively:
- Collaborating with talented professionals
- Finding a mentor who is 2-5 years ahead
- Taking on ambitious projects outside of your comfort zone
Hard work can only take you so far, meanwhile leveraging a network and daring to take on challenges will 10x your growth.
I have curated the best interview resources to crack Data Science Interviews
👇👇
https://topmate.io/analyst/1024129
Like if you need similar content 😄👍
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Python Cheatsheet-4.pdf1.53 MB
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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
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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/
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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
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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.
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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.
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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.
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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.
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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]
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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
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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.
