Coding Interview Resources
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This channel contains the free resources and solution of coding problems which are usually asked in the interviews. Managed by: @love_data
显示更多📈 Telegram 频道 Coding Interview Resources 的分析概览
频道 Coding Interview Resources (@crackingthecodinginterview) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 51 978 名订阅者,在 技术与应用 类别中位列第 2 553,并在 印度 地区排名第 6 635 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 51 978 名订阅者。
根据 04 十一月, 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 -224,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 2.23%。内容发布后 24 小时内通常能获得 0.60% 的反应,占订阅者总量。
- 帖子覆盖: 每篇帖子平均可获得 1 158 次浏览,首日通常累积 312 次浏览。
- 互动与反馈: 受众积极参与,单帖平均反应数为 1。
- 主题关注点: 内容集中在 array, stack, algorithm, programming, sort 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:
“This channel contains the free resources and solution of coding problems which are usually asked in the interviews.
Managed by: @love_data”
凭借高频更新(最新数据采集于 05 十一月, 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。
51 978
订阅者
-1224 小时
-237 天
-22430 天
帖子存档
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Building_Python_Web_APIs_with_FastAPI_A_fast_paced_guide_to_building.pdf9.19 MB
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Various types of test used in statistics for data science
T-test: used to test whether the means of two groups are significantly different from each other.
ANOVA: used to test whether the means of three or more groups are significantly different from each other.
Chi-squared test: used to test whether two categorical variables are independent or associated with each other.
Pearson correlation test: used to test whether there is a significant linear relationship between two continuous variables.
Wilcoxon signed-rank test: used to test whether the median of two related samples is significantly different from each other.
Mann-Whitney U test: used to test whether the median of two independent samples is significantly different from each other.
Kruskal-Wallis test: used to test whether the medians of three or more independent samples are significantly different from each other.
Friedman test: used to test whether the medians of three or more related samples are significantly different from each other.
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