AI and Machine Learning

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Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses

India3 005 Education1 547...

📈 Analytical overview of Telegram channel AI and Machine Learning

Channel AI and Machine Learning (@machine_learning_courses) in the English language segment is an active participant. Currently, the community unites 94 077 subscribers, ranking 1 547 in the Education category and 3 005 in the India region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 94 077 subscribers.

According to the latest data from 26 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 965 over the last 30 days and by 37 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 6.79%. Within the first 24 hours after publication, content typically collects 2.34% reactions from the total number of subscribers.
Post reach: On average, each post receives 6 384 views. Within the first day, a publication typically gains 2 203 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, llm, linkedin, linux, udemy.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses”

Thanks to the high frequency of updates (latest data received on 27 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.

94 077

Subscribers

+3724 hours

+2267 days

+96530 days

6 384

Post views

~ 2 20324 hours

~ 2 91648 hours

6.79%

Engagement rate

~ 1

Posts per day

Ads index

beta

Posts Archive

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10. Appendix A Introduction To Cyber Security - Part 02

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10. Appendix A Introduction To Cyber Security - Part 01

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09. AI Security Risks

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08. AI For Malware Detection

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07. AI In Network Security - Part 02

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07. AI In Network Security - Part 01

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06. Building A Phishing Detection System With AI - Part 02

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06. Building A Phishing Detection System With AI - Part 01

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05. Building An Email Filtering System With AI - Part 03

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05. Building An Email Filtering System With AI - Part 02

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05. Building An Email Filtering System With AI - Part 01

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04. Where Is AI Used In Cyber Security Today - Part 02

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04. Where Is AI Used In Cyber Security Today - Part 01

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03. New Age Of Social Engineering

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02. ChatGPT For Cyber SecurityEthical Hacking

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01. Introduction To The Course

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🔰 Artificial Intelligence & ChatGPT for Cyber Security 2024 🌟 4.6 - 1597 votes 💰 Original Price: $49.99

📖 Master Cyber Security/Ethical Hacking With Artificial Intelligence - Implement, Uncover Risks and Navigate The AI Era

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Use simple prompts to create Agents that are expert on your codebase with Potpie AI. 🤖 Perform debugging, testing, system design etc. in a fully autonomous way using these agents. It's free and open source - try now! 🔥 Get started with Potpie AI

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🔔 Knock Knock 🔔 Do you know someone committing a crime around You? @Report him anonymously and Get paid. We accept Reports for ✅ Crypto Scammers ✅ Cyber Crime ✅ Tax Crime 🧾 Learn more at @Lexcura ✉️ Start Your Report

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💸 Understanding Popular ML Algorithms: 1️⃣ Linear Regression: Think of it as drawing a straight line through data points to predict future outcomes. 2️⃣ Logistic Regression: Like a yes/no machine - it predicts the likelihood of something happening or not. 3️⃣ Decision Trees: Imagine making decisions by answering yes/no questions, leading to a conclusion. 4️⃣ Random Forest: It's like a group of decision trees working together, making more accurate predictions. 5️⃣ Support Vector Machines (SVM): Visualize drawing lines to separate different types of things, like cats and dogs. 6️⃣ K-Nearest Neighbors (KNN): Friends sticking together - if most of your friends like something, chances are you'll like it too! 7️⃣ Neural Networks: Inspired by the brain, they learn patterns from examples - perfect for recognizing faces or understanding speech. 8️⃣ K-Means Clustering: Imagine sorting your socks by color without knowing how many colors there are - it groups similar things. 9️⃣ Principal Component Analysis (PCA): Simplifies complex data by focusing on what's important, like summarizing a long story with just a few key points.