MNIST is used as example in tensorflow. Here are the examples of how to use logistic regression and KNN(K nearest neighbors) to analyze this data.

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It is to provide an online IFRS9/CECL lifetime credit loss calculation engine.

use linear regression and logistic regression as examples to show how gradient descent is used to minimize the loss function or to maximize the target function.

在3中我们介绍了怎么使用TensorFlow做多元回归。本文使用一个图文结合的具体例子详细说明怎么做。下一篇我们将会沿用4中所说的办法介绍怎么做logistic regression.做线性回归和logistic regression不是tf的特长。tf的特长是用各种神经网络做深度学习。我们将会在后几篇陆续介绍。

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convolution matrix is the most import conception in cnn. Here is a simple introduction of convolve, correlate and some image processing basic techs in numpy.

This is an example of variable selection in linear regression(and it can be easily applied in logistic regression). It has two steps:

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suppose we want to calculate the weighted average probability of default of all risk rating weighted by the number of borrowers on each pd risk rating(or a little more, grouped by industry or portfolio), we need this weighted average function on each group. Pandas has groupby to split data, and then apply function to calculate and summarize.