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 292 388 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 1 290 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 292 388 名订阅者。
根据 08 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 -6 274,过去 24 小时变化为 -221,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 7.46%。内容发布后 24 小时内通常能获得 5.47% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 21 812 次浏览,首日通常累积 16 003 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 159。
- 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 09 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。
292 388
订阅者
-22124 小时
-1 3547 天
-6 27430 天
帖子存档
292 347
How to train an algorithm to successfully pass the "Sonic The Hedgehog" game? Sergey Kolesnikov together with his team took the 4th place out of 900+ in the Open AI contest, and now is telling how to reach it. https://medium.com/swlh/at-the-speed-of-reinforcement-learning-an-openai-contest-story-6ed34fe7a3bb
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Comparison of top data science libraries for Python, R and Scala [Infographic]
https://medium.com/activewizards-machine-learning-company/comparison-of-top-data-science-libraries-for-python-r-and-scala-infographic-574069949267
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RTX 2080 Ti Deep Learning Benchmarks https://lambdalabs.com/blog/2080-ti-deep-learning-benchmarks/
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Необычные материалы в робототехнике.
У каждого робота должен быть блестящий металлический зад, это знают все. Но в реальных роботах металла не так уж и много — с ним соседствуют пластики, композиты и силикон, а порой и совсем нестандартные субстанции: http://amp.gs/hCG8
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@robotics_channel — канал о робототехнике, искусственном разуме и сферах их применения. Регулярные новости, статьи, вакансии, обучающие курсы и полезные ресурсы.
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SeqGAN: GANs for sequence generation https://medium.com/prathena/seqgan-gans-for-sequence-generation-2099a85baed0
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Brilliant post on #CS and #Software about strategy and psychology of Software Development, which is highly applicable to Data Science too.
“Imaginary Problems Are the Root of Bad Software”
https://medium.com/s/story/imaginary-problems-d4f2921bd1b8
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Two Sigma: Using News to Predict Stock Movements
Use news analytics to predict stock price performance
1st place - $25,000
2nd place - $20,000
3rd place - $15,000
4th through 7th place - $10,000 each
This is a two-stage competition consisting of a Submission period and a Scoring period. In the Submission period, entrants will train their models in Kaggle Kernels. During the Scoring period, models submitted at the end of the submission period will be evaluated against regularly updated news and market data.
Start Date: 9/25/2018
Rules Acceptance/Team Merger Deadline: 1/2/2019
Submission Deadline: 1/8/2019 After this date, we will not be taking any more submissions. You can sit back and watch the leaderboard unfold. Remember to select your two best submissions to be rescored. In this competition we will not auto-select your two submissions.
End Date: 7/15/2019
https://www.kaggle.com/c/two-sigma-financial-news
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Geoffrey Hinton: The Foundations of Deep Learning https://www.youtube.com/watch?v=zl99IZvW7rE
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How to Develop 1D Convolutional Neural Network Models for Human Activity Recognition https://machinelearningmastery.com/cnn-models-for-human-activity-recognition-time-series-classification/
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deep learning object detection
A paper list of object detection using deep learning.
https://github.com/hoya012/deep_learning_object_detection
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Machine Learning Crash Course
with TensorFlow APIs https://developers.google.com/machine-learning/crash-course/
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A new understanding of Batch Normalization https://medium.com/@geetankr/a-new-understanding-of-batch-normalization-e11e05e120dc
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How to Model Human Activity From Smartphone Data https://machinelearningmastery.com/how-to-model-human-activity-from-smartphone-data/
