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。

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：

一、为什么Kaggle

Kaggle是目前最大的数据科学竞赛与技能分享平台。在Kaggle上你可以查找和发布数据集，探索和构建模型，与其他数据科学家和机器学习工程师合作，并参加竞赛以解决数据科学挑战。参加Kaggle竞赛，你至少可以有以下几种收获：

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 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) $

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.

We need to rely on pyodbc, the sample code is as belows.

Why embedding

Natural language processing systems traditionally treat words as discrete atomic symbols, and this may lead to some obstacles in word preprocessing: