Machine Learning with Python
前往频道在 Telegram
Learn Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers. Admin: @HusseinSheikho || @Hussein_Sheikho
显示更多📈 Telegram 频道 Machine Learning with Python 的分析概览
频道 Machine Learning with Python (@codeprogrammer) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 67 810 名订阅者,在 教育 类别中位列第 2 427,并在 印度 地区排名第 5 028 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 67 810 名订阅者。
根据 13 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 60,过去 24 小时变化为 -3,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 4.31%。内容发布后 24 小时内通常能获得 1.69% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 2 926 次浏览,首日通常累积 1 148 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 6。
- 主题关注点: 内容集中在 insidead, learning, degree, evaluation, algorithm 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 Machine Learning with hands-on Python tutorials, real-world code examples, and clear explanations for researchers and developers.
Admin: @HusseinSheikho || @Hussein_Sheikho”
凭借高频更新(最新数据采集于 14 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。
67 810
订阅者
-324 小时
-77 天
+6030 天
帖子存档
📱 Gemini with 3.25 billion parameters can be run locally on your computer directly in a Chrome tab,
This version runs without internet, is completely free, private and uses less than 2 GB of RAM. It only takes two lines of code to run Gemini, as shown in the third video.
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🔺 Data science learning roadmap in 2024
👨🏻💻 If you want to start learning data science from scratch in 2024, this roadmap can be a great starting point for you.👌🏼
1️⃣ Basics of data science
🏷 Statistics and probability
◾┘️ link: Statistics & Probability
🏷 Linear Algebra
┘ ◽️ link: Essence of Linear Algebra
2️⃣ Programming language
🏷 Python
◾┘️ link: Learn Python 3
3️⃣ Data analysis and manipulation
🏷 Pandas library
◾┘️ link: pandas documentation
🏷 Data preparation with Pandas
Link : Data Wrangling with Pandas
🏷 NumPy library
◾┘️ link: NumPy documentation
4️⃣ Data visualization
🏷 Matplotlib and Seaborn library
◾┘️ Link: Matplotlib / seaborn
🏷 Tableau Public platform
Link : Tableau Public
5️⃣ Principles of machine learning
🏷 scikit-learn library
◾┘️ link: scikit-learn
6️⃣ Learning algorithms
🏷 Hands-On Machine Learning book
◾┘️ link: Hands-On ML
7️⃣ Deep learning
🏷 TensorFlow library
◾┘️ link: TensorFlow Tutorial
🏷 PyTorch library
◾┘️ Link: PyTorch Documentation
8️⃣ Big data technologies
🏷 Spark framework course
◾┘️ Link: Spark Course
9️⃣ Advanced topics
🏷 Natural language processing course in Python
◾┘️ link: NLP in Python
1️⃣ Share your projects on Kaggle and GitHub
🏷 Kaggle platform
◾┘️ link: Kaggle
🏷 GitHub platform
◾┘️ Link: GitHub
⭐️ http://t.me/codeprogrammer
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Understand the fundamental concepts and techniques of web scraping and its legal and ethical considerations.
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Discover how Gen AI revolutionizes the web scraping landscape with real-world examples.
3️⃣ Jina Reader API:
Get acquainted with the Jina Reader API, a powerful tool for obtaining LLM-friendly input from URLs or web searches.
4️⃣ ScrapeGraphAI:
Dive into ScrapeGraphAI, a groundbreaking Python library that combines LLMs and direct graph logic for creating robust scraping pipelines.
Event Details:
🗓 Date: 22 June, Saturday
⏰ Time: 11:00 AM IST
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Connect with Founder from IIT Delhi;
https://www.linkedin.com/in/satvik-paramkusham/
🔺 Data science learning roadmap in 2024
👨🏻💻 If you want to start learning data science from scratch in 2024, this roadmap can be a great starting point for you.👌🏼
1️⃣ Basics of data science
🏷 Statistics and probability
◾┘️ link: Statistics & Probability
🏷 Linear Algebra
┘ ◽️ link: Essence of Linear Algebra
2️⃣ Programming language
🏷 Python
◾┘️ link: Learn Python 3
3️⃣ Data analysis and manipulation
🏷 Pandas library
◾┘️ link: pandas documentation
🏷 Data preparation with Pandas
Link : Data Wrangling with Pandas
🏷 NumPy library
◾┘️ link: NumPy documentation
4️⃣ Data visualization
🏷 Matplotlib and Seaborn library
◾┘️ Link: Matplotlib / seaborn
🏷 Tableau Public platform
Link : Tableau Public
5️⃣ Principles of machine learning
🏷 scikit-learn library
◾┘️ link: scikit-learn
6️⃣ Learning algorithms
🏷 Hands-On Machine Learning book
◾┘️ link: Hands-On ML
7️⃣ Deep learning
🏷 TensorFlow library
◾┘️ link: TensorFlow Tutorial
🏷 PyTorch library
◾┘️ Link: PyTorch Documentation
8️⃣ Big data technologies
🏷 Spark framework course
◾┘️ Link: Spark Course
9️⃣ Advanced topics
🏷 Natural language processing course in Python
◾┘️ link: NLP in Python
1️⃣ Share your projects on Kaggle and GitHub
🏷 Kaggle platform
◾┘️ link: Kaggle
🏷 GitHub platform
◾┘️ Link: GitHub
🔺 Data science learning roadmap in 2024
✅ If you want to start learning data science from scratch in 2024, this roadmap can be a great starting point for you.
1️⃣ Basics of data science
🏷 Statistics and probability
◾️┘️ link: Statistics & Probability
🏷 Linear Algebra
◾️┘️ link: Essence of Linear Algebra
2️⃣ Programming language
🏷 Python
◾️┘️ link: Learn Python 3
3️⃣ Data analysis and manipulation
🏷 Pandas library
◾️┘️ link: pandas documentation
🏷 Data preparation with Pandas
◾️┘️ Link : Data Wrangling with Pandas
🏷 NumPy library
◾️┘️ link: NumPy documentation
4️⃣ Data visualization
🏷 Matplotlib and Seaborn library
◾️┘️ Link: Matplotlib / seaborn
🏷 Tableau Public platform
◾️┘️ Link : Tableau Public
5️⃣ Principles of machine learning
🏷 scikit-learn library
◾️┘️ link: scikit-learn
6️⃣ Learning algorithms
🏷 Hands-On Machine Learning book
◾️┘️ link: Hands-On ML
7️⃣ Deep learning
🏷 TensorFlow library
◾️┘️ link: TensorFlow Tutorial
🏷 PyTorch library
◾️┘️ Link: PyTorch Documentation
8️⃣ Big data technologies
🏷 Spark framework course
◾️┘️ Link: Spark Course
9️⃣ Advanced topics
🏷 Natural language processing course in Python
◾️┘️ link: NLP in Python
1️⃣ Share your projects on Kaggle and GitHub
🏷 Kaggle platform
◾️┘️ link: Kaggle
🏷 GitHub platform
◾️┘️ Link: GitHub
🔺 10 free MIT data science courses
☄️ If you have started learning data science, improve your learning level right now with the courses of prestigious universities and institutions in the world such as Stanford, Harvard and MIT, which are the first in the field of data science.
✅ Here I have put the top 10 free MIT data science courses for you in 2024. 👇
🏷 MIT University's free data science courses
┤ ✅ Computational thinking and data science introductory course
┤ ✅ machine learning course with Python
┤ ✅ Computer science and programming course with Python
┤ ✅ Supply chain analysis course
┤ ✅ Understanding the world through data course
┤ ✅ Computational thinking course for modeling and simulation
┤ ✅ Probability Course - Science of Uncertainty and Data
┤ ✅ The course of principles of production processes
┤ ✅ Principles and basics of statistics and probability course
┘ ✅ The course of becoming an entrepreneur
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🔺 10 free MIT data science courses
☄️ If you have started learning data science, improve your learning level right now with the courses of prestigious universities and institutions in the world such as Stanford, Harvard and MIT, which are the first in the field of data science.
✅ Here I have put the top 10 free MIT data science courses for you in 2024. 👇
🏷 MIT University's free data science courses
┤ ◼️ Computational thinking and data science introductory course
┤ ◻️ machine learning course with Python
┤ ◼️ Computer science and programming course with Python
┤ ◻️ Supply chain analysis course
┤ ◼️ Understanding the world through data course
┤ ◻️ Computational thinking course for modeling and simulation
┤ ◼️ Probability Course - Science of Uncertainty and Data
┤ ◻️ The course of principles of production processes
┤ ◼️ Principles and basics of statistics and probability course
┘ ◻️ The course of becoming an entrepreneur
现已上线!2025 年 Telegram 研究 — 年度关键洞察 
