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

Network:Free Courses with Certificate - Python Programming, Data Science, Java Coding, SQL, Web Development, AI, ML, ChatGPT Expert India7 029 Education3 254...

📈 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 53 207 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 53 207 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.

53 207

Subscribers

+3524 hours

+1927 days

+1 05030 days

3 086

Post views

~ 89224 hours

~ 1 13048 hours

5.80%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

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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.

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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.

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

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#meme

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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 main function when the user clicks "Get Answer"

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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.

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

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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

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

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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

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

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

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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): ⬇️

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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......

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Machine_Learning_in_Finance_From_Theory_to_Practice_Matthew_F_Dixon.pdf8.75 MB

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

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Matrix Theory and Linear Algebra Peter Selinger, 2018