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Pythonlearnerr

Pythonlearnerr

前往频道在 Telegram

Learn Python Programming at Free of cost With Projects ☑️

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印度2 334教育1 202

📈 Telegram 频道 Pythonlearnerr 的分析概览

频道 Pythonlearnerr (@pythonlearnerr) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 110 108 名订阅者，在 教育 类别中位列第 1 202，并在 印度 地区排名第 2 334 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 110 108 名订阅者。

根据 25 八月, 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 -2 069，过去 24 小时变化为 -69，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 9.77%。内容发布后 24 小时内通常能获得 1.86% 的反应，占订阅者总量。
  • 帖子覆盖： 每篇帖子平均可获得 10 766 次浏览，首日通常累积 2 047 次浏览。
  • 互动与反馈： 受众积极参与，单帖平均反应数为 54。
  • 主题关注点： 内容集中在 certification, stack, physicswallah, internship, sql 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 Python Programming at Free of cost With Projects ☑️”

凭借高频更新（最新数据采集于 26 八月, 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。

110 108
订阅者
-6924 小时
-4747 天
-2 06930 天
帖子存档
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𝗔𝗿𝗲 𝘆𝗼𝘂 𝗿𝗲𝗮𝗱𝘆? Build the skills top AI teams hire for — from intelligent ag…","articleBody":"💡 𝗔𝗜 𝗶𝘀 𝗿𝗲𝘀𝗵𝗮𝗽𝗶𝗻𝗴 𝗲𝘃𝗲𝗿𝘆 𝗶𝗻𝗱𝘂𝘀𝘁𝗿𝘆. 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WiFi Passwords Source Code (2) (1).py0.01 KB

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Sometimes reality outpaces expectations in the most unexpected ways. While global AI development seems increasingly fragmented, Sber just released Europe's largest open-source AI collection—full weights, code, and commercial rights included. ✅ No API paywalls. ✅ No usage restrictions. ✅ Just four complete model families ready to run in your private infrastructure, fine-tuned on your data, serving your specific needs. What makes this release remarkable isn't merely the technical prowess, but the quiet confidence behind sharing it openly when others are building walls. Find out more in the article from the developers. GigaChat Ultra Preview: 702B-parameter MoE model (36B active per token) with 128K context window. Trained from scratch, it outperforms DeepSeek V3.1 on specialized benchmarks while maintaining faster inference than previous flagships. Enterprise-ready with offline fine-tuning for secure environments. GitHub | HuggingFace | GitVerse GigaChat Lightning offers the opposite balance: compact yet powerful MoE architecture running on your laptop. It competes with Qwen3-4B in quality, matches the speed of Qwen3-1.7B, yet is significantly smarter and larger in parameter count. Lightning holds its own against the best open-source models in its class, outperforms comparable models on different tasks, and delivers ultra-fast inference—making it ideal for scenarios where Ultra would be overkill and speed is critical. Plus, it features stable expert routing and a welcome bonus: 256K context support. GitHub | Hugging Face | GitVerse Kandinsky 5.0 brings a significant step forward in open generative models. The flagship Video Pro matches Veo 3 in visual quality and outperforms Wan 2.2-A14B, while Video Lite and Image Lite offer fast, lightweight alternatives for real-time use cases. The suite is powered by K-VAE 1.0, a high-efficiency open-source visual encoder that enables strong compression and serves as a solid base for training generative models. This stack balances performance, scalability, and practicality—whether you're building video pipelines or experimenting with multimodal generation. GitHub | GitVerse | Hugging Face | Technical report Audio gets its upgrade too: GigaAM-v3 delivers speech recognition model with 50% lower WER than Whisper-large-v3, trained on 700k hours of audio with punctuation/normalization for spontaneous speech. GitHub | HuggingFace | GitVerse Every model can be deployed on-premises, fine-tuned on your data, and used commercially. It's not just about catching up – it's about building sovereign AI infrastructure that belongs to everyone who needs it.

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Tune in to the 10th AI Journey 2025 international conference: scientists, visionaries, and global AI practitioners will come together on one stage. Here, you will hear the voices of those who don't just believe in the future—they are creating it! Speakers include visionaries Kai-Fu Lee and Chen Qufan, as well as dozens of global AI gurus from around the world! On the first day of the conference, November 19, we will talk about how AI is already being used in various areas of life, helping to unlock human potential for the future and changing creative industries, and what impact it has on humans and on a sustainable future. On November 20, we will focus on the role of AI in business and economic development and present technologies that will help businesses and developers be more effective by unlocking human potential. On November 21, we will talk about how engineers and scientists are making scientific and technological breakthroughs and creating the future today! Ride the wave with AI into the future! Tune in to the AI Journey webcast on November 19-21.

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Legend Form Complete Source Code 👇 ----------------------------------------------------- <html> <head> <style> .outer{  margin:auto; height:300px; width:400px; border:2px solid black; position:relative } p{ margin-left:80px; } .in{ margin-left:80px; padding:10px } #bt{ margin-top:20px; position:absolute; left:150px; } #bt:hover{ background:green; font-size:13px; cursor:pointer; color:white; } </style> <script> function fa(){ if(a.value=="" || b.value==""){ f() document.getElementById("a").style.border="3px solid red" document.getElementById("b").style.border="3px solid red" bt.value="Pahila data tak" } else{ document.getElementById("a").style.border="3px solid green" document.getElementById("b").style.border="3px solid green" bt.value="Ha thik ahe ata" bt.style.left="120px"; } } flag=1 function f(){ if(flag==1){ bt.style.left="210px" flag=2 } else if(flag==2){ bt.style.left="80px" flag=1 } } </script> </head> <body> <div class="outer"> <h1 style="text-align:center">Legend form</h1> <p>Enter Id</p> <input class="in" type="text" placeholder="Enter id" id="a"/> <p>Enter Confirm Pass</p> <input class="in" type="password" placeholder="Enter password" id="b"/> <br> <input type="submit" onmouseenter="fa()" onclick="alert('waaaa')" id="bt" /> </div> </body> </html>

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Coding Games In Python .pdf30.48 MB

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Python Projects Source Codes

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WiFi Passwords Source Code (2).py0.01 KB

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Coding Games In Python (2).pdf30.48 MB

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Python Handwritten Notes PDF Guide (1).pdf32.34 MB