Feng's Notes Isn't coding fun?

The guide to predictive data analysis on MIMIC

Below is my teaching materials when I served as assistant teacher on Digital Health and data analysis at Reading University. The dataset I used for this course is MIMIC. If you are interested in healthcare data analysis, this might be what you want to check.

Kaggle竞赛指南 —— 问题求解套路


Kaggle竞赛指南 —— 探索性数据分析


Kaggle竞赛指南 —— 数据预处理

数据预预处理对于机器学习结果来说是至关重要,有时甚至是决定性的。本篇我们将讨论针对不同的数据类型,如何根据不同的数据模型来做预处理。具体我们将讨论四种最常见类型的数据,分别是 数字数据,类别数据,时间数据和坐标数据。

Kaggle竞赛指南 —— 主流机器学习算法

目前竞赛中(其实也是常规实际问题)的主流算法有四大门类: Linear, Tree-based, kNN 以及 Neural Networks 下面分别简单介绍一下:

Kaggle竞赛指南 —— 简介



Backward propagation of Neural Network explained

Backpropagation is the foundation of the deep neural network. Usually, we consider it to be kind of ‘dark magic’ we are not able to understand. However, it should not be the black box which we stay away. In this article, I will try to explain backpropagation as well as the whole neural network step by step in the original mathematical way.

Stochastic gradient descent

Stochastic Gradient decent is one of the fundamental algorithm in deep learning. It is used when we perform optimization of the cost function.Suppose the function is $ f(x) $


[Pandas]How to plot counts of each value

[Pandas]How to calculate datetime difference in years

Suppose you got a person’s regist time in one column and his birth date in another column, now you need to calculate his age when he did the registration. There are two ways to reach this result.