ch
Feedback
Libros de Programación

Libros de Programación

前往频道在 Telegram

Libros en pdf sobre programación, informática, hacking, carding, etc. Apoya por PayPal https://paypal.me/jctc01 @openve

显示更多

📈 Telegram 频道 Libros de Programación 的分析概览

频道 Libros de Programación (@libpro) 西班牙语 语言赛道中的 是活跃参与者。目前社区聚集了 19 383 名订阅者,在 技术与应用 类别中位列第 6 950,并在 委内瑞拉 地区排名第 235

📊 受众指标与增长动态

невідомо 创建以来,项目保持高速增长,吸引了 19 383 名订阅者。

根据 15 六月, 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 -97,过去 24 小时变化为 12,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 15.86%。内容发布后 24 小时内通常能获得 3.85% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 3 075 次浏览,首日通常累积 747 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 22
  • 主题关注点: 内容集中在 lenguaje, learn, microsoft, c++, sitio 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:
Libros en pdf sobre programación, informática, hacking, carding, etc. Apoya por PayPal https://paypal.me/jctc01 @openve

凭借高频更新(最新数据采集于 17 六月, 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。

19 388
订阅者
+1224 小时
+167
-9730
帖子存档
http://jdebp.eu./FGA/operating-system-books.html A book list for operating system kernel developers and device driver writers

https://www.math.auckland.ac.nz/~sgal018/crypto-book/main.pdf Mathematics of Public Key Cryptography. Version 2.0 Steven D Galbraith October 31, 2018 696 pp

Michael_Kerrisk_The_Linux_programming.pdf6.92 MB

Michael Kerrisk-The Linux programming interface_ a Linux and UNIX system programming handbook-No Starch Press (2010)
Michael Kerrisk-The Linux programming interface_ a Linux and UNIX system programming handbook-No Starch Press (2010)

ANSI_Common_Lisp_-_Paul_Graham.pdf5.85 MB

On LISP Advanced Techniques for Common LISP - Paul Graham.pdf1.06 MB

Edmund_Weitz_Common_Lisp_Recipes_.pdf8.04 MB

photo content

paip.pdf17.45 MB

Common_lisp_touretzky.pdf1.08 MB

Land of Lisp.epub8.29 MB

https://ins.jku.at/sites/default/files/thesis/MasterThesis_Hengstberger_2016.pdf Steganography in file systems for mobile environments with plausible deniability

Linux Device Drivers Development(2017).epub1.80 MB

Clojure for the Brave and True(2015).pdf6.63 MB

https://arxiv.org/pdf/1811.04288.pdf IP Geolocation through Reverse DNS Ovidiu Dan, Vaibhav Parikh, Brian D. Davison (Submitted on 10 Nov 2018) IP Geolocation databases are widely used in online services to map end user IP addresses to their geographical locations. However, they use proprietary geolocation methods and in some cases they have poor accuracy. We propose a systematic approach to use publicly accessible reverse DNS hostnames for geolocating IP addresses. Our method is designed to be combined with other geolocation data sources. We cast the task as a machine learning problem where for a given hostname, we generate and rank a list of potential location candidates. We evaluate our approach against three state of the art academic baselines and two state of the art commercial IP geolocation databases. We show that our work significantly outperforms the academic baselines, and is complementary and competitive with commercial databases. To aid reproducibility, we open source our entire approach.

Statistics for Machine Learning_with Python and R-(2017).epub12.06 MB