Telegram RegisterThe public register of Telegram

Channel

TDS走向数据科学

@nvxingai

On this record: Growth · Engagement · Posts · Citations · Cite this entry

60subscribers

-1 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1002415714394
TypeChannel
Username@nvxingai
CreatedBetween 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded10 August 2026
Last confirmed live13 August 2026
Measurements held3
Confirmed unchanged1 time, most recently 13 August 2026
On Telegramt.me/nvxingai

Growth

606160.56 August 2026 — 61 subscribers10 August 2026 — 61 subscribers13 August 2026 — 60 subscribers6 August 202613 August 2026
3 measurements spanning 7 days, net -1. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 60–61 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
13 Aug 2026, 12:4860-1
10 Aug 2026, 04:1661no change
6 Aug 2026, 19:5261first reading

Engagement

20 posts held, back to 4 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.75%
avg views ÷ 60 subscribers
Avg views / post
1.6
20 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
20
of 20 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 10 August 2026
Posts held20 (4 August 202610 August 2026)
Views total33
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken10 Aug 2026, 04:16 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Recent posts

10 Aug 2026, 04:06 UTC1 viewsread 10 August 2026
Photo

❤️欢迎来到 TGRSS —— Telegram 上最智能、最全能的 RSS 自动内容矩阵! 在这里,你不需要手动刷新网页、不需要下载 App、不需要错过任何热点。 TGRSS 通过实时 RSS 订阅 + 自动化推送,为你打造了一个“内容永不缺席”的私人信息流: 实时全球新闻:科技、财经、国际大事,一秒不落 成人专区(18+):精选故事、幽默、亲密建议与行业动态(纯链接推送,安全隐私优先) [❤️‍🔥赞助商]TGFOX矩阵机器人 👩🏻‍⚕️广告投放: @TGRSS123 🚀支持200+频道同时投放,所有频道每天推送一次

9 Aug 2026, 04:18 UTC2 viewsread 10 August 2026
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来自速搜推荐 @SSOU 📢奥运会金牌-奥运会投注-... 📢万利平台 PA平台 万利... 📢福布斯平台 福布斯真人 ... 📢欧博私网 欧博包杀 亚星... 📢欧博官网🅱️欧博私网�... 📢UG环球平台 UG环球真... 📢换妻 绿帽 媚黑 📢换妻 绿帽优选 📢利博代理 利博百家乐 利... 📢🇹🇼夢夢台灣中價位茶... 📢搞笑小品站 📢亚星私网 欧博私网 亚星... 📢菲律宾新闻情报局 📢经典动漫|热门动漫|动漫... 📢皇冠招商 皇冠娱乐 亚星... 👉流量互推规则介绍💥 以下是广告推荐 📢⚽️注册送138🧧百家乐/棋牌/电竞体育信誉平台 📢 X-panel 一站式拉人增粉平台 📢 TeleTop 中文索引 📢球速体育相信品牌的力量、老品牌值得信赖、不限ip、免实名。 📢⚽️爱博体育-佣金55%-玩家首存即升VIP7等级⚽️ 🇨🇳 简体中文包 —————————-- 🔥将 @TonGroupHelpBot 设置

8 Aug 2026, 15:03 UTC2 viewsread 10 August 2026
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在 Q、K 和 V 之前:重构 Transformer |走向数据科学 许多 Transformer 解释者都是从完成的架构开始的。我们问为什么它看起来是这样的。 Sankar Srinivasan | towardsdatascience​.com • Aug 8, 2026

8 Aug 2026, 13:02 UTC2 viewsread 10 August 2026
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为 My LangGraph AI Agent 构建 Streamlit UI |走向数据科学 为有状态的 LangGraph 代理构建生产就绪的 Web 界面 Soner Yıldırım | towardsdatascience​.com • Aug 8, 2026

7 Aug 2026, 16:49 UTC2 viewsread 10 August 2026
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Matplotlib 与 Plotly:您应该选择哪种 Python 图表工具? |走向数据科学 从静态图到交互式数据探索 Thomas Reid | towardsdatascience​.com • Aug 7, 2026

7 Aug 2026, 15:21 UTC1 viewsread 10 August 2026
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列表问题的循环工程:当答案是每一段而不是最上面的一段时走向数据科学 企业文档智能 [Vol.1 #12] - 大多数 RAG 管道默默失败的问题类别,以及处理这些问题的管道形状 angela shi | towardsdatascience​.com • Aug 7, 2026

7 Aug 2026, 13:33 UTC1 viewsread 10 August 2026
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pandas 的问题不在于性能。这是认知开销。 |走向数据科学 更快的数据帧引擎固然很好,但它们并不能减少分析师必须记住的语法量。 Neal Hughes | towardsdatascience​.com • Aug 7, 2026

7 Aug 2026, 12:22 UTC1 viewsread 10 August 2026
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我的跌倒检测模型得分为 94%,它在骗我 |走向数据科学 单一评估选择如何将我的结果夸大了 25 分,以及重建诚实地教会了我关于人们可能依赖的 ML 系统的知识 Ramandeep Singh | towardsdatascience​.com • Aug 7, 2026

6 Aug 2026, 16:49 UTC1 viewsread 10 August 2026
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我构建了一个人工智能数据代理,可以查询数据并回答业务问题。方法如下。 |走向数据科学 构建数据代理和对话界面的分步指南,让业务用户无需 SQL 即可以自然语言探索数据 Jiayan Yin | towardsdatascience​.com • Aug 6, 2026

6 Aug 2026, 15:19 UTC1 viewsread 10 August 2026
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上个月的机器学习经验教训 |走向数据科学 会议旅行的缺点 Pascal Janetzky | towardsdatascience​.com • Aug 6, 2026

6 Aug 2026, 13:47 UTC1 viewsread 10 August 2026
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我用 Python 构建了一个工具调用代理。这是我调试它的方法|走向数据科学 在添加代理框架之前,具有真实 API 调用、验证、紧凑输出和跟踪证据的最小循环 Abdullahi Dattijo | towardsdatascience​.com • Aug 6, 2026

6 Aug 2026, 12:18 UTC1 viewsread 10 August 2026
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交叉引用的循环工程:当 RAG 回答“参见第 7.2 节”而不是实际答案时 |走向数据科学 企业文档智能 [Vol.1 #11] - 当第一个答案指向文档中的其他位置时,管道循环返回以获取链接的上下文 angela shi | towardsdatascience​.com • Aug 6, 2026

Showing the 12 most recent of 20 posts we hold for @nvxingai. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Citation-graph rank

Citation-graph rank — 731,337 of 1,189,255entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Mentions

Named by 25 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 13 August 2026 — this entry's latest reading, not the date you are reading this.

“TDS走向数据科学” (@nvxingai), 60 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/nvxingai.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.