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 292 652 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 292 652 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。
292 652
订阅者
-20924 小时
-1 3687 天
-6 31730 天
帖子存档
292 657
30 Data Science Punchlines
A holiday reading list condensed into 30 quotes
https://towardsdatascience.com/data-science-conversation-starters-84affd2347f6
292 657
The major advancements in Deep Learning in 2018
https://tryolabs.com/blog/2018/12/19/major-advancements-deep-learning-2018/
292 657
Facebook has released #PyText — new framework on top of #PyTorch.
This framework is build to make it easier for developers to build #NLP models.
https://code.fb.com/ai-research/pytext-open-source-nl..
Github: https://github.com/facebookresearch/pytext
292 657
Machine Learning Top 10 Articles for the Past Month (v.Dec 2018)
https://medium.mybridge.co/machine-learning-top-10-articles-for-the-past-month-v-dec-2018-37b229f930a1
292 657
Train Neural Networks With Noise to Reduce Overfitting
https://machinelearningmastery.com/train-neural-networks-with-noise-to-reduce-overfitting/
292 657
So, is your algorithm not working?
https://towardsdatascience.com/so-is-your-algorithm-not-working-aa8e4ebd2066
292 657
How to Stop Training Deep Neural Networks At the Right Time Using Early Stopping
https://machinelearningmastery.com/how-to-stop-training-deep-neural-networks-at-the-right-time-using-early-stopping/
292 657
A Gentle Introduction to Early Stopping to Avoid Overtraining Deep Learning Neural Network Models
https://machinelearningmastery.com/early-stopping-to-avoid-overtraining-neural-network-models/
292 657
Great took for neural network, deep learning and machine learning models visualization.
https://github.com/lutzroeder/netron
292 657
Forensic Deep Learning: Kaggle Camera Model Identification Challenge
https://towardsdatascience.com/forensic-deep-learning-kaggle-camera-model-identification-challenge-f6a3892561bd
292 657
NHL Analytics: Shots, Rebounds, and Weak Signals
https://towardsdatascience.com/nhl-analytics-shots-rebounds-and-weak-signals-c293ba8c635f
292 657
Digit Recognizer - Introduction to Kaggle Competitions with Image Classification Task (0.995)
https://towardsdatascience.com/digit-recognizer-introduction-to-kaggle-competitions-with-image-classification-task-0-995-268fa2b90e13
292 657
Attention, Dialogue, and Learning Reusable Patterns
https://medium.com/rasa-blog/attention-dialogue-and-learning-reusable-patterns-5d6bd18ef9f0
292 657
Data Science for Real
Transforming property management with advanced analytics and machine learning
https://towardsdatascience.com/data-science-for-real-c09f088b6550
292 657
9 obscure Python libraries for data science
https://opensource.com/article/18/11/python-libraries-data-science
292 657
No time to read AI research? We summarized top 2018 papers for you
https://www.topbots.com/most-important-ai-research-papers-2018/
