Going for Gold: Predicting medal outcomes in the Olympics using Generalized Linear Modeling
https://towardsdatascience.com/going-for-gold-predicting-medal-outcomes-in-the-olympics-using-generalized-linear-modeling-e6e9d4837ae8
https://towardsdatascience.com/going-for-gold-predicting-medal-outcomes-in-the-olympics-using-generalized-linear-modeling-e6e9d4837ae8
Medium
Going for Gold: Predicting medal outcomes in the Olympics using Generalized Linear Modeling
A fun introduction to GLMs using an Olympics dataset
Fastapi框架-(16)docker-compose容器编排(前)篇-单独启动多容器再串联提供服务(不建议仅学习参考)
https://juejin.cn/post/6993236118955114503
https://juejin.cn/post/6993236118955114503
juejin.cn
Fastapi框架-(16)docker-compose容器编排(前)篇-单独启动多容器再串联提供服务(不建议仅学习参考)
番外篇: 从前面几个实践的示例看,我们的自己构建的py3的镜像其实是超级大的。一不小心就把C盘给吃的差不多了!所以接下来首先就是考虑,能不能使用最小的镜像来作为我们的运行的容器呐?这个不管怎么样还是得