[PYTHON] Summary of articles posted so far (statistics / machine learning / mathematics etc.)

It's been a long time since I posted it, @ kenmatsu4: blush: It's been a while, but it's not a new post but a summary of the articles so far: sweat_smile: It's been half a year since I said I'd write a summary around the end of last year, but I'll finally release it. I tried to categorize it into statistics, machine learning, programming, math, and more.

Statistics

Category Title

General [Statistics] First "standard deviation" (to avoid frustration with statistics) < / strong>

A description of the standard deviation for those who are completely unfamiliar with statistics. We will start with the explanation of the Σ symbol.

General Basics of Statistics

Lecture slides on the basics of statistics. (With Python code that draws the graph)

General Understanding the meaning of complex and bizarre normal distribution formulas

If you look closely at the formula for the normal distribution, you can see that this formula is meaningful.

General [Statistics] Let's visualize the relationship between the normal distribution and the chi-square distribution.

The chi-square distribution is closely related to the normal distribution.

General [Statistics] Grasp the image of the central limit theorem with a graph

I will explain with a graph what the central limit theorem, which is said to be the most important theorem in statistics, is.

General [Statistics] What is the likelihood? Let's explain graphically.

I will explain the likelihood that is difficult to read. It's not a dog degree w

General [Statistics] Understand what an ROC curve is by animation.

I will explain the ROC curve, which is a difficult concept, with animation.

General [Statistics] Understand the mechanism of Q-Q plot by animation.

I will explain the mechanism of Q-Q plot, which is a more difficult concept, using animation.

Regression analysis Explanation of the concept of regression analysis using Python Part 1

I will explain how the logic for drawing lines in regression analysis works.

Regression analysis Explanation of the concept of regression analysis using python Part 2

I will explain how the logic for drawing lines in regression analysis works.

Regression analysis Explanation of the concept of regression analysis using Python Extra 1

I will explain how the logic for drawing lines in regression analysis works.

Regression analysis [Statistics] Visualization for understanding Generalized Linear Mixed Models (GLMM).

Animated explanation of a complex generalized linear mixed model with multiple distributions.

Regression analysis [Statistics] [R] Try using quantile regression.

Introducing regression analysis using quantiles (75% quantiles, etc.) instead of means.

Regression analysis [Statistics] Try to draw a regression line with the feeling that there may be outliers < / strong>

Introducing the R library that handles outliers well.

MCMC [Statistics] Let's explain sampling by Markov chain Monte Carlo method (MCMC) with animation.

We will explain the operating principle of MCMC using animation.

MCMC [Statistics] Visualize and understand the Hamiltonian Monte Carlo method with animation.

This is an article that explains the Hamiltonian Monte Carlo method, which is an improvement of the Metropolis-Hastings method, using animation.

MCMC [Statistics] Let's explain the execution of logistic regression in stan in detail (w / Titanic dataset)

This is also a demonstration using the MCMC library Stan.

MCMC [Statistics] Multiprocessing of MCMC sampling

This is a code explanation for parallelizing MCMC sampling and making effective use of multi-core.

Principal component analysis Principal component analysis Analyze handwritten numbers using PCA. Part 1

Let's do principal component analysis with a handwritten digit dataset.

Principal component analysis Principal component analysis Analyze handwritten numbers using PCA. Part 2

Let's try the main component Bunsei with a handwritten digit data set.

Time series analysis Implementation of particle filter by Python and application to state space model

This is an explanation of the mechanism of the particle filter, which is an online version of MCMC for estimating the state space model.

Time series analysis Call dlm from python to run a time-varying coefficient regression model td>

This is a state-space model that expresses a model in which the regression coefficient changes over time.

Time series analysis [Statistics] [Time series analysis] Plot the ARMA model to grasp the tendency.

This is an article to get a feel for plotting the relationship between the parameters of the time series model ARMA and the shape of the graph.

Category	Title
General	[Statistics] First "standard deviation" (to avoid frustration with statistics) < / strong>
A description of the standard deviation for those who are completely unfamiliar with statistics. We will start with the explanation of the Σ symbol.
General	Basics of Statistics
Lecture slides on the basics of statistics. (With Python code that draws the graph)
General	Understanding the meaning of complex and bizarre normal distribution formulas
If you look closely at the formula for the normal distribution, you can see that this formula is meaningful.
General	[Statistics] Let's visualize the relationship between the normal distribution and the chi-square distribution.
The chi-square distribution is closely related to the normal distribution.
General	[Statistics] Grasp the image of the central limit theorem with a graph
I will explain with a graph what the central limit theorem, which is said to be the most important theorem in statistics, is.
General	[Statistics] What is the likelihood? Let's explain graphically.
I will explain the likelihood that is difficult to read. It's not a dog degree w
General	[Statistics] Understand what an ROC curve is by animation.
I will explain the ROC curve, which is a difficult concept, with animation.
General	[Statistics] Understand the mechanism of Q-Q plot by animation.
I will explain the mechanism of Q-Q plot, which is a more difficult concept, using animation.
Regression analysis	Explanation of the concept of regression analysis using Python Part 1
I will explain how the logic for drawing lines in regression analysis works.
Regression analysis	Explanation of the concept of regression analysis using python Part 2
I will explain how the logic for drawing lines in regression analysis works.
Regression analysis	Explanation of the concept of regression analysis using Python Extra 1
I will explain how the logic for drawing lines in regression analysis works.
Regression analysis	[Statistics] Visualization for understanding Generalized Linear Mixed Models (GLMM).
Animated explanation of a complex generalized linear mixed model with multiple distributions.
Regression analysis	[Statistics] [R] Try using quantile regression.
Introducing regression analysis using quantiles (75% quantiles, etc.) instead of means.
Regression analysis	[Statistics] Try to draw a regression line with the feeling that there may be outliers < / strong>
Introducing the R library that handles outliers well.
MCMC	[Statistics] Let's explain sampling by Markov chain Monte Carlo method (MCMC) with animation.
We will explain the operating principle of MCMC using animation.
MCMC	[Statistics] Visualize and understand the Hamiltonian Monte Carlo method with animation.
This is an article that explains the Hamiltonian Monte Carlo method, which is an improvement of the Metropolis-Hastings method, using animation.
MCMC	[Statistics] Let's explain the execution of logistic regression in stan in detail (w / Titanic dataset)
This is also a demonstration using the MCMC library Stan.
MCMC	[Statistics] Multiprocessing of MCMC sampling
This is a code explanation for parallelizing MCMC sampling and making effective use of multi-core.
Principal component analysis	Principal component analysis Analyze handwritten numbers using PCA. Part 1
Let's do principal component analysis with a handwritten digit dataset.
Principal component analysis	Principal component analysis Analyze handwritten numbers using PCA. Part 2
Let's try the main component Bunsei with a handwritten digit data set.
Time series analysis	Implementation of particle filter by Python and application to state space model
This is an explanation of the mechanism of the particle filter, which is an online version of MCMC for estimating the state space model.
Time series analysis	Call dlm from python to run a time-varying coefficient regression model td>
This is a state-space model that expresses a model in which the regression coefficient changes over time.
Time series analysis	[Statistics] [Time series analysis] Plot the ARMA model to grasp the tendency.
This is an article to get a feel for plotting the relationship between the parameters of the time series model ARMA and the shape of the graph.

Machine learning

Category Title

General Thorough explanation of EM algorithm

Using the mixed Gaussian distribution as a theme, we will carefully explain the EM algorithm, which is a well-known algorithm in the machine learning area.

General Thorough explanation of EM algorithm (bonus) ~ In case of MAP estimation ~

In addition to the above explanation, I will explain a little about how to apply MAP estimation.

General Explain what stochastic gradient descent is by using Python >

Animated explanation of stochastic gradient descent, one of the optimization algorithms.

General [Machine learning] What is the LP norm?

Try to understand by illustrating the LP norm that you do not know at first glance.

General [Machine learning] Summary and execution of model evaluation / indicators (w / Titanic dataset)

It's sober, but it's important to measure the performance of the model properly. It is a commentary for that.

General [Machine learning] OOB (Out-Of-Bag) and its ratio

This is also plain, but it's an interesting story that the number of Napiers $ e $ was hidden behind the bootstrap sampling.

General Derivation of Kullback Leibler Divergence for multivariate normal distribution

Explains the details of the calculation when the multivariate normal distribution is applied to the probability model of Kullback-Leibler divergence.

Handwritten numbers Playing handwritten numbers with python Part 1

This is an article to play with MNIST, a dataset of handwritten numbers that everyone often uses.

Handwritten numbers Play handwritten numbers with python Part 2 (identify)

Try to identify handwritten characters by the template matching method.

Handwritten numbers [Machine learning] Write the k-nearest neighbor method (k-nearest neighbor method) in python by yourself. Recognize handwritten numbers

A better way to identify handwritten characters using the k-nearest neighbor method.

Deep Learning [Machine learning] I will explain while trying the deep learning framework Chainer.

The better performance, Neural Network, is used to identify handwritten characters.

Deep Learning [Deep learning] Try Autoencoder with Chainer and visualize the result.

Try to figure out who the AutoEncoder used in Deep Learning is.

Deep Learning Variational Autoencoder Thorough Explanation

I explained in detail the Variational Autoencoder (VAE), which is the basic model of the generative model generated by Deep Learning.

Spark MLlib [Machine learning] Start Spark with iPython Notebook and try MLlib < / td>

Environment settings for using Spark's machine learning library MLlib.

Spark MLlib [Machine learning] Try running Spark MLlib with Python and make recommendations

Let's make a recommendation using MLlib.

Spark MLlib [Machine learning] Cluster Yahoo News articles with MLlib topic model (LDA).

We will also try the topic model of the topic with MLlib.

Anomaly detection [Machine learning] "Anomaly detection and change detection Chapter 1" Fill in the space between the lines of the Neyman-Pearson lemma See

I tried to fill the space between the lines of the formula in the anomaly detection book.

Anomaly detection [Machine learning] "Anomaly detection and change detection" Let's draw the figure of Chapter 1 in Python.

I drew a graph to improve the understanding of the anomaly detection book.

Anomaly detection Use R density ratio estimation package densratio from Python

Calling R package from Python I tried to detect anomaly using rpy2 and R density ratio estimation package dens ratio.

sparse [PyStan] Try Graphical Lasso with Stan

Graphical Lasso is an article to confirm with Stan that it is a multivariate normal distribution in which the Laplace distribution is set as the prior distribution of the precision matrix.

Summary Machine Learning Professional Series Round Reading Session Slide Summary

A collection of slides used in machine learning study sessions. I recommend it because there are many good materials!

Category	Title
General	Thorough explanation of EM algorithm
Using the mixed Gaussian distribution as a theme, we will carefully explain the EM algorithm, which is a well-known algorithm in the machine learning area.
General	Thorough explanation of EM algorithm (bonus) ~ In case of MAP estimation ~
In addition to the above explanation, I will explain a little about how to apply MAP estimation.
General	Explain what stochastic gradient descent is by using Python >
Animated explanation of stochastic gradient descent, one of the optimization algorithms.
General	[Machine learning] What is the LP norm?
Try to understand by illustrating the LP norm that you do not know at first glance.
General	[Machine learning] Summary and execution of model evaluation / indicators (w / Titanic dataset)
It's sober, but it's important to measure the performance of the model properly. It is a commentary for that.
General	[Machine learning] OOB (Out-Of-Bag) and its ratio
This is also plain, but it's an interesting story that the number of Napiers $ e $ was hidden behind the bootstrap sampling.
General	Derivation of Kullback Leibler Divergence for multivariate normal distribution
Explains the details of the calculation when the multivariate normal distribution is applied to the probability model of Kullback-Leibler divergence.
Handwritten numbers	Playing handwritten numbers with python Part 1
This is an article to play with MNIST, a dataset of handwritten numbers that everyone often uses.
Handwritten numbers	Play handwritten numbers with python Part 2 (identify)
Try to identify handwritten characters by the template matching method.
Handwritten numbers	[Machine learning] Write the k-nearest neighbor method (k-nearest neighbor method) in python by yourself. Recognize handwritten numbers
A better way to identify handwritten characters using the k-nearest neighbor method.
Deep Learning	[Machine learning] I will explain while trying the deep learning framework Chainer.
The better performance, Neural Network, is used to identify handwritten characters.
Deep Learning	[Deep learning] Try Autoencoder with Chainer and visualize the result.
Try to figure out who the AutoEncoder used in Deep Learning is.
Deep Learning	Variational Autoencoder Thorough Explanation
I explained in detail the Variational Autoencoder (VAE), which is the basic model of the generative model generated by Deep Learning.
Spark MLlib	[Machine learning] Start Spark with iPython Notebook and try MLlib < / td>
Environment settings for using Spark's machine learning library MLlib.
Spark MLlib	[Machine learning] Try running Spark MLlib with Python and make recommendations
Let's make a recommendation using MLlib.
Spark MLlib	[Machine learning] Cluster Yahoo News articles with MLlib topic model (LDA).
We will also try the topic model of the topic with MLlib.
Anomaly detection	[Machine learning] "Anomaly detection and change detection Chapter 1" Fill in the space between the lines of the Neyman-Pearson lemma See
I tried to fill the space between the lines of the formula in the anomaly detection book.
Anomaly detection	[Machine learning] "Anomaly detection and change detection" Let's draw the figure of Chapter 1 in Python.
I drew a graph to improve the understanding of the anomaly detection book.
Anomaly detection	Use R density ratio estimation package densratio from Python
Calling R package from Python I tried to detect anomaly using rpy2 and R density ratio estimation package dens ratio.
sparse	[PyStan] Try Graphical Lasso with Stan
Graphical Lasso is an article to confirm with Stan that it is a multivariate normal distribution in which the Laplace distribution is set as the prior distribution of the precision matrix.
Summary	Machine Learning Professional Series Round Reading Session Slide Summary
A collection of slides used in machine learning study sessions. I recommend it because there are many good materials!

Programming

Category Title

Twitter Get a large amount of Starbucks Twitter data with python and try data analysis Part 1 strong>

Try using Python to call Twitter's REST API to save the data.

Twitter Get a large amount of Starbucks Twitter data with python and try data analysis Part 2 strong>

Separate spam from the retrieved Twitter data.

Twitter Get a large amount of Starbucks Twitter data with python and try to analyze the data Part 3 strong>

Let's analyze the reason why the number of tweets increased after one day.

Twitter Visualization and analysis of Starbucks Twitter data location information

Visualize the location information hidden in Twitter.

Twitter Attempt a rudimentary sentiment analysis on Twitter Stream API data.

Try to analyze emotions using the Japanese evaluation polarity dictionary.

Twitter Get information on the 100 most influential tech Twitter users in the world with python.

This is a scraping study.

Convenience book Private Python handbook (updated from time to time)

I have a handy book of Python tricks that I often use.

Graphics Preferences for generating animated GIFs from Python on Mac

This is a method I often use, a setting method for generating animations.

Graphics Video conversion process by moviepy with ndarray

I will explain the procedure for processing videos. It is used when the video is subjected to deep learning and the result is further output as a video.

Graphics [Python] Customize Colormap when drawing graphs with matplotlib

This is a trick when you want to adjust the color of the graph exquisitely.

Cython Using Cython with Jupyter Notebook [Python]

This is an explanation of how to try Cython speedup on Jupyter Notebook.

Word Cloud Visualize the word appearance frequency of sentences with Word Cloud. [Python]

This is an explanation of how to make it possible to understand words that are often displayed in a certain sentence at a glance.

Graph DB Introduction to Graph Database Neo4j in Python for Beginners (for Mac OS X)

I tried a new type of database graph database.

Julia Try running Julia with Jupyter for regression analysis.

I explained from installation to execution of regression analysis in the popular programming language Julia.

Category	Title
Twitter	Get a large amount of Starbucks Twitter data with python and try data analysis Part 1 strong>
Try using Python to call Twitter's REST API to save the data.
Twitter	Get a large amount of Starbucks Twitter data with python and try data analysis Part 2 strong>
Separate spam from the retrieved Twitter data.
Twitter	Get a large amount of Starbucks Twitter data with python and try to analyze the data Part 3 strong>
Let's analyze the reason why the number of tweets increased after one day.
Twitter	Visualization and analysis of Starbucks Twitter data location information
Visualize the location information hidden in Twitter.
Twitter	Attempt a rudimentary sentiment analysis on Twitter Stream API data.
Try to analyze emotions using the Japanese evaluation polarity dictionary.
Twitter	Get information on the 100 most influential tech Twitter users in the world with python.
This is a scraping study.
Convenience book	Private Python handbook (updated from time to time)
I have a handy book of Python tricks that I often use.
Graphics	Preferences for generating animated GIFs from Python on Mac
This is a method I often use, a setting method for generating animations.
Graphics	Video conversion process by moviepy with ndarray
I will explain the procedure for processing videos. It is used when the video is subjected to deep learning and the result is further output as a video.
Graphics	[Python] Customize Colormap when drawing graphs with matplotlib
This is a trick when you want to adjust the color of the graph exquisitely.
Cython	Using Cython with Jupyter Notebook [Python]
This is an explanation of how to try Cython speedup on Jupyter Notebook.
Word Cloud	Visualize the word appearance frequency of sentences with Word Cloud. [Python]
This is an explanation of how to make it possible to understand words that are often displayed in a certain sentence at a glance.
Graph DB	Introduction to Graph Database Neo4j in Python for Beginners (for Mac OS X)
I tried a new type of database graph database.
Julia	Try running Julia with Jupyter for regression analysis.
I explained from installation to execution of regression analysis in the popular programming language Julia.

Mathematics, etc.

Category Title

Mathematics [Mathematics] If you understand the meaning of "inner product" graphically, you can see various things 1 < / strong>

The inner product can be calculated, but some people may not immediately think of a pictorial image. This article is a commentary for understanding the dot product graphically.

Mathematics [Mathematics] Let's visualize what eigenvalues and eigenvectors are. / td>

I think some of you may find it difficult to get a pictorial image of the eigenvalues and eigenvectors. This is also an article that I tried to explain using a lot of animation.

Mathematics Intuitive understanding of Jensen's inequality

This is an article that shows how Jensen's inequality regarding random variables can be understood graphically.

Mathematics The meaning of fractional division understood in pizza

It's a little bit of a story ..., but I really like it.

Summary [Qiita API] [Statistics / Machine Learning] I tried to summarize and analyze the articles posted so far.

It's a little old, but I analyzed the data of the article I wrote.

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Category	Title
Mathematics	[Mathematics] If you understand the meaning of "inner product" graphically, you can see various things 1 < / strong>
The inner product can be calculated, but some people may not immediately think of a pictorial image. This article is a commentary for understanding the dot product graphically.
Mathematics	[Mathematics] Let's visualize what eigenvalues and eigenvectors are. / td>
I think some of you may find it difficult to get a pictorial image of the eigenvalues and eigenvectors. This is also an article that I tried to explain using a lot of animation.
Mathematics	Intuitive understanding of Jensen's inequality
This is an article that shows how Jensen's inequality regarding random variables can be understood graphically.
Mathematics	The meaning of fractional division understood in pizza
It's a little bit of a story ..., but I really like it.
Summary	[Qiita API] [Statistics / Machine Learning] I tried to summarize and analyze the articles posted so far.
It's a little old, but I analyzed the data of the article I wrote.