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

Ko'proq ko'rsatish

Hindiston3 005 Taʼlim1 547...

📈 Telegram kanali AI and Machine Learning analitikasi

AI and Machine Learning (@machine_learning_courses) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 94 077 obunachidan iborat bo'lib, Taʼlim toifasida 1 547-o'rinni va Hindiston mintaqasida 3 005-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 94 077 obunachiga ega bo‘ldi.

26 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 965 ga, so‘nggi 24 soatda esa 37 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

Tasdiqlash holati: Tasdiqlanmagan
Jalb etish (ER): Auditoriya o‘rtacha 6.79% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 2.34% ini tashkil etuvchi reaksiyalarni to‘playdi.
Post qamrovi: Har bir post o‘rtacha 6 384 marta ko‘riladi; birinchi sutkada odatda 2 203 ta ko‘rish yig‘iladi.
Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 9 ta reaksiya keladi.
Tematik yo‘nalishlar: Kontent learning, llm, linkedin, linux, udemy kabi asosiy mavzularga jamlangan.

📝 Tavsif va kontent siyosati

Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses”

Yuqori yangilanish chastotasi (oxirgi ma’lumot 27 Iyun, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Taʼlim toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.

94 077

Obunachilar

+3724 soatlar

+2267 kunlar

+96530 kunlar

6 384

Post ko'rishlar

~ 2 20324 soatlar

~ 2 91648 soatlar

6.79%

Muloqot nisbati

~ 1

Kuniga postlar

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Postlar arxiv

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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.