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AI and Machine Learning

AI and Machine Learning

前往频道在 Telegram

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

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印度3 020教育1 561

📈 Telegram 频道 AI and Machine Learning 的分析概览

频道 AI and Machine Learning (@machine_learning_courses) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 94 021 名订阅者，在 教育 类别中位列第 1 561，并在 印度 地区排名第 3 020 位。

📊 受众指标与增长动态

自 невідомо 创建以来，项目保持高速增长，吸引了 94 021 名订阅者。

根据 24 六月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 986，过去 24 小时变化为 67，整体触达仍然可观。

  • 认证状态： 未认证
  • 互动率 (ER)： 平均受众互动率为 6.50%。内容发布后 24 小时内通常能获得 1.56% 的反应，占订阅者总量。
  • 帖子覆盖： 每篇帖子平均可获得 6 109 次浏览，首日通常累积 1 470 次浏览。
  • 互动与反馈： 受众积极参与，单帖平均反应数为 8。
  • 主题关注点： 内容集中在 learning, llm, linkedin, linux, udemy 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台：
“Learn Data Science, Data Analysis, Machine Learning, Artificial Intelligence, and Python with Tensorflow, Pandas & more! Buy ads: https://telega.io/c/machine_learning_courses”

凭借高频更新（最新数据采集于 25 六月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 教育 类别中的关键影响点。

94 021
订阅者
+6724 小时
+1517 天
+98630 天
帖子存档
AI and Machine Learning
AI and Machine Learning
94 021
📌 PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks 🗂 Category: DEEP LEARNING 🕒 Date: 2
📌 PyTorch Explained: From Automatic Differentiation to Training Custom Neural Networks 🗂 Category: DEEP LEARNING 🕒 Date: 2025-09-24 | ⏱️ Read time: 15 min read Deep learning is shaping our world as we speak. In fact, it has been slowly… 🔗 Read Full Article

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Andrew Tate - The Real World Courses: ✔️Andrew Tate - AI Campus ✔️Andrew Tate - Body Language ✔️Andrew Tate - Chess ✔️Andrew Tate - Fitness ✔️Andrew Tate - Hustler University ✔️Andrew Tate - Iron Mind ✔️Andrew Tate - Network Brilliance ✔️Arno About ✔️Copywriting ✔️Cryptocurrency ✔️E-Commerce ✔️Freelancing ✔️Life Lessons from Luc ✔️Peak Performance ✔️Tate Answers Questions ✔️Business Mastery ✔️Amazon FBA ✔️Stocks 🔗 Sales Page: https://www.jointherealworld.com/checkout Original Price (Subscription): $49.99/monthly or $149/3 months or $497/1 year
Files will be provided separately so that you can download just what you need.
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AI and Machine Learning
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🔗 Building a Conventional Neural Network (CNNs) from Scratch 🕒 Date: 2024-11-05 | ⏱️ Read time: 15 min read Line-by-Line, L
🔗 Building a Conventional Neural Network (CNNs) from Scratch 🕒 Date: 2024-11-05 | ⏱️ Read time: 15 min read
Line-by-Line, Let’s Build a ResNet Classifier on the MNIST-Fashion Dataset
🔗 Read Full Article

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📦 Exercise Files

AI and Machine Learning
AI and Machine Learning
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📱Artificial intelligence 📱Fine-Tuning for LLMs: from Beginner to Advanced

AI and Machine Learning
AI and Machine Learning
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📂 Full description This course capitalizes on the latest advancements in Large Language Models (LLMs) like FLAN-T5, enabling professionals to harness these tools effectively in the rapidly-evolving AI landscape. Instructor Axel Sirota helps you establish a strong foundation in the basics of LLMs, exploring their architecture, evolution, and role in the current AI landscape. Delve into prompt engineering and learn how to craft effective prompts that guide LLM outputs for specific tasks. Then deep dive into transfer learning and PEFT fine-tuning using LoRA and find out how to adapt and optimize LLMs for varied NLP tasks. Each course section comprises live-action clips, slides, and demos, as well as real-world challenges covering prompt engineering, transfer learning, and fine-tuning techniques to enhance FLAN-T5's capabilities. Plus, youll complete a final project focused on building an NLP solution encompassing sentiment analysis, text summarization, and question answering.

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🔅 Fine-Tuning for LLMs: from Beginner to Advanced 🌐 Author: Axel Sirota 🔰 Level: Advanced ⏰ Duration: 3h 25m 🌀 Gain the e
🔅 Fine-Tuning for LLMs: from Beginner to Advanced 🌐 Author: Axel Sirota 🔰 Level: Advanced ⏰ Duration: 3h 25m
🌀 Gain the expertise you need in Large Language Models (LLMs), a rapidly evolving field in AI, including hands-on practice.
📗 Topics: Large Language Models, Generative AI, Fine Tuning 📤 Join Artificial intelligence for more courses

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🇦🇺 A Black Mirror scenario is actually coming true An Australian bank employee spent 25 years at her job, then taught artif
🇦🇺 A Black Mirror scenario is actually coming true An Australian bank employee spent 25 years at her job, then taught artificial intelligence to perform her tasks: writing responses, correcting errors, and refining skills. After mastering everything, the AI “graduated” and told her: “Thank you, I will take over” — with the next decision being to fire her.

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💡 How to use AI to learn anything faster
💡 How to use AI to learn anything faster

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💡 RAG Best Practices
💡 RAG Best Practices

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🔗 Machine Learning Roadmap Whether you're just starting out or looking to refine your skills, this Machine Learning Roadmap
🔗 Machine Learning Roadmap
Whether you're just starting out or looking to refine your skills, this Machine Learning Roadmap breaks down every step
1️⃣ Build a solid foundation in math and stats 2️⃣ Dive into ML algorithms like Linear Regression, SVM, and Clustering 3️⃣ Choose your ML focus, from supervised learning to recommender systems 4️⃣ Master popular libraries like PyTorch, TensorFlow, and Scikit-learn 5️⃣ Gain real-world experience with projects and side gigs

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What is RAG? 🤖📚 RAG stands for Retrieval-Augmented Generation. It’s a technique where an AI model first retrieves relevant
What is RAG? 🤖📚 RAG stands for Retrieval-Augmented Generation. It’s a technique where an AI model first retrieves relevant info (like from documents or a database), and then generates an answer using that info. 🧠 Think of it like this: Instead of relying only on what it "knows", the model looks things up first - just like you would Google something before replying. 🔍 Retrieval + 📝 Generation = Smarter, up-to-date answers!

AI and Machine Learning
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Mastering LLMs is a journey, and our infographic gives you a sneak peek into the key steps to success. From fundamentals to d
Mastering LLMs is a journey, and our infographic gives you a sneak peek into the key steps to success. From fundamentals to deployment, it’s all about having the right roadmap.

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📌13 ai tools to finish months of work in minutes! 1. Image Generator ⇢ leonardo.ai 2. Writing & Automation ⇢ blaze.today 3.
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🔗 3 Types of Machine Learning
🔗 3 Types of Machine Learning

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🔺 AI bots built their own toxic social network Researchers created a platform of 500 AI chatbots modeled on U.S. demographic
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⚡️ 200+ ready-made scripts for n8n Found a simple and useful resource: a GitHub repository with 200+ free workflows for n8n.
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