• ## Cross entropy loss function NN. Cross entropy loss ()

Time：2021-6-22

nn.CrossEntropyLoss() 1. Introduction When using pytorch deep learning framework to do multi classification, the cross entropy loss function NN. Crossentropyloss () 2. Information quantity and entropy Amount of information:It is used to measure the uncertainty of an event; The greater the probability of an event, the smaller the uncertainty, the smaller the amount of information […]

• ## The visualization of data probability distribution in MATLAB

Time：2021-3-13

Matlab visualization, we sometimes through data statistics and can not know or clear what kind of data distribution, this paper is based on this situation, the distribution of data to do a simple probability distribution of visualization, interested users to understand it! Software name: Matlab r2017b 64 bit Chinese Special Edition (with cracking file + […]

• ## Algorithm Engineering 3. Mathematical basis, probability theory and statistics

Time：2021-1-28

Traditional machine learning can be said to use probability theory everywhere. probability theory 1. Total probability formula and Bayesian formula Total probability formula$$P(A)=\sum\limits_{j=1}^{n}P(B_j)P(A|B_j)$$Bayes formula$$P(B_i|A)=\dfrac{P(A,B_i)}{P(A)}=\dfrac{P(B_i)P(A|B_i)}{\sum\limits_{j=1}^{n}P(B_j)P(A|B_j)}$$Bayesian formula is the core tool of Bayesian statistics. Bayesian school thinks that the probability of event occurrence is not as simple as frequency school, but should add human priors, so that […]

• ## Algorithm engineering lion VI. frequency school and Bayesian school

Time：2021-1-17

Frequency school and Bayes school are two different schools. Frequency school thinks that the probability of events is completely determined by the existing data;The Bayesian school thinks that the probability of the occurrence of the event itself conforms to a certain probability distribution, and this distribution is determined subjectively, which is also called a priori […]

• ## Algorithm engineering lion six, frequency school and Bayesian school

Time：2020-12-22

Frequency school and Bayesian school are two different schools. The frequency school thinks that the probability of an event is completely determined by the existing data;The Bayesian school thinks that the probability of events itself conforms to a certain probability distribution, and this distribution is determined by human beings, which is called prior distribution.The representative […]

• ## Data science statistics: what is skewness?

Time：2020-11-25

By Abhishek SharmaCompile | VKSource | analytics vidhya summary Skewness is an important statistical concept in data science and analysis Understand what skewness is and why it’s important for you as a data science professional introduce The concept of skewness has been integrated into our way of thinking. When we see an image, our brain […]

• ## Mathematical foundation probability theory and statistics

Time：2020-10-29

The traditional machine learning can be said to use probability theory everywhere. probability theory 1. Total probability formula and Bayes formula Total probability formula$$P(A)=\sum\limits_{j=1}^{n}P(B_j)P(A|B_j)$$Bayes formula$$P(B_i|A)=\dfrac{P(A,B_i)}{P(A)}=\dfrac{P(B_i)P(A|B_i)}{\sum\limits_{j=1}^{n}P(B_j)P(A|B_j)}$$Bayesian formula is the core weapon of Bayesian statistics. Bayesian school believes that the probability of events is not as simple as frequency school, but should be added to human prior, […]

• ## Automatic driving positioning system unscented Kalman filter

Time：2020-9-12

Unscented Kalman filter is another way to solve nonlinear Kalman filter. It uses unscented transform to solve the problem of nonlinear transformation of probability distribution. Unscented Kalman filter does not need to calculate Jacobin matrix like extended Kalman filter, and it can obtain more accurate nonlinear processing effect under the condition of approximately the same […]

• ## Text generation (seq2seq)

Time：2020-8-19

Problem: generated according to the style of the specified text. For example, the romance of the Three Kingdoms How to achieve it? First of all, we need to understandLanguage model。 What is a language model? The language model is a given sequence to predict the probability distribution of the next token.It’s like cloze, but the […]

• ## Distilling the knowledge in a neural network

Time：2020-8-4

Distilling the knowledge in a neural network Author: Zhi Guangda 1. Concept introduction “Many insects are best at extracting energy and nutrients from the environment when they are in larval form, but when they grow into adults, they need to be good at completely different abilities, such as migration and reproduction.” In the paper of […]

• ## Probability theory in deep learning

Time：2020-5-2

This article starts with the official account number: RAIS, and expects your attention. Preface This series of articles is the reading notes of deep learning, which can be read together with the original book for better effect. probability theory In machine learning, we often need to deal with a large number of uncertain quantities or […]

• ## Information theory in deep learning

Time：2020-4-26

This article starts with the official account number: RAIS, welcome your attention. Preface This series of articles is the reading notes of deep learning, which can be read together with the original book for better effect. information theory Information theory is a branch of mathematics, which is very important. You can see that the information […]