现已上线！2025 年 Telegram 研究 — 年度关键洞察 
Machinelearning
前往频道在 Telegram
Погружаемся в машинное обучение и Data Science Показываем как запускать любые LLm на пальцах. По всем вопросам - @haarrp @itchannels_telegram -🔥best channels Реестр РКН: clck.ru/3Fmqri
显示更多📈 Telegram 频道 Machinelearning 的分析概览
频道 Machinelearning (@ai_machinelearning_big_data) 俄语 语言赛道中的 是活跃参与者。目前社区聚集了 292 747 名订阅者，在 技术与应用 类别中位列第 328，并在 俄罗斯 地区排名第 1 291 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 292 747 名订阅者。
根据 07 七月, 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 -6 317，过去 24 小时变化为 -209，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 7.45%。内容发布后 24 小时内通常能获得 5.46% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 21 817 次浏览，首日通常累积 15 977 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 160。
- 主题关注点： 内容集中在 openai, claude, api, gemini, контекст 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：
“Погружаемся в машинное обучение и Data Science
Показываем как запускать любые LLm на пальцах.
По всем вопросам - @haarrp
@itchannels_telegram -🔥best channels
Реестр РКН: clck.ru/3Fmqri”
凭借高频更新（最新数据采集于 08 七月, 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 技术与应用 类别中的关键影响点。
292 747
订阅者
-20924 小时
-1 3687 天
-6 31730 天
帖子存档
292 707
Debugging your tensorflow code right (without so many painful mistakes)
https://towardsdatascience.com/debugging-your-tensorflow-code-right-without-so-many-painful-mistakes-b48bd9145d5c?source=collection_home---4------0---------------------
292 707
How to Improve Performance With Transfer Learning for Deep Learning Neural Networks
https://machinelearningmastery.com/how-to-improve-performance-with-transfer-learning-for-deep-learning-neural-networks/
292 707
Intuitive Deep Learning Part 1a: Introduction to Neural Networks
What is Deep Learning? A very gentle and intuitive introduction to Neural Networks and how they work!
https://towardsdatascience.com/intuitive-deep-learning-part-1a-introduction-to-neural-networks-aaeb3a1500df
292 707
The Best of AI: New Articles Published This Month (January 2019)
10 data articles handpicked by the Sicara team, just for you
https://blog.sicara.com/01-2019-best-ai-new-articles-this-month-8e2113fbd17b
292 707
How to build AutoML from scratch
https://medium.com/@alxmamaev/how-to-build-automl-from-scratch-ce45a4b51e0f
292 707
Designing non-linear navigation for machine learning and topic modeling experiences
https://uxdesign.cc/designing-non-linear-navigation-for-machine-learning-and-topic-modeling-experiences-4ee969875ebe
292 707
MIT Deep Learning Basics: Introduction and Overview with TensorFlow
https://medium.com/tensorflow/mit-deep-learning-basics-introduction-and-overview-with-tensorflow-355bcd26baf0?linkId=63206779
292 707
Improving Evolutionary Strategies with Generative Neural Networks
https://arxiv.org/abs/1901.11271
292 707
Искусственные нейронные сети выращивают навигационные клетки как в мозге
https://habr.com/ru/post/438526/
292 707
Predicting Kickstarter Campaign Success with Gradient Boosted Decision Trees: A Machine Learning Classification Problem
https://medium.com/@rileypredum/predicting-kickstarter-campaign-success-with-gradient-boosted-decision-trees-a-machine-learning-23077436c5f7
292 707
Browse state-of-the-art
509 leaderboards • 963 tasks • 700 datasets • 8598 papers with code
https://paperswithcode.com/sota
292 707
292 707
Interactive Controls in Jupyter Notebooks
How to use interactive IPython widgets to enhance data exploration and analysis
https://towardsdatascience.com/interactive-controls-for-jupyter-notebooks-f5c94829aee6
292 707
How to build an image classifier with greater than 97% accuracy
https://medium.freecodecamp.org/how-to-build-the-best-image-classifier-3c72010b3d55
292 707
Lessons Learned from Kaggle’s Airbus Challenge
https://medium.com/@YassineAlouini/lessons-learned-from-kaggles-airbus-challenge-252e25c5efac?source=topic_page---------19------------------1
292 707
Google Researchers Have a New Alternative to Traditional Neural Networks
Say hello to the capsule network.
https://www.technologyreview.com/the-download/609297/google-researchers-have-a-new-alternative-to-traditional-neural-networks/
