# Notebook Gallery

Links to the best IPython and Jupyter Notebooks.

#### Textual Analysis of XPN's AtoZ Playlist

At present I must point out that this is all very preliminary

#### Machine Learning

The text is released under the CC-BY-NC-ND license , and code is released under the MIT license . If you find this content useful, please consider supporting the work by buying the book !

#### High-Performance Pandas: eval() and query()

The text is released under the CC-BY-NC-ND license , and code is released under the MIT license . If you find this content useful, please consider supporting the work by buying the book !

#### This website does not host notebooks, it only renders notebooks available on other websites.

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#### Hierarchical Partial Pooling

So, suppose a player came to bat only 4 times, and never hit the ball. Are they a bad player?

#### Reinforcement Learning

The basic structure of a reinforcement learning problem is:

#### Survival Analysis using Python

Tutorial provided for class FP MD 6107 - Survival Analysis

#### Setup

This website does not host notebooks, it only renders notebooks available on other websites.

#### Congressional Elections, Logistic Regression, and Feature Selection

For comparison's sake, I'll begin by specifying a logistic model with features that I pick without any empirical evidence to back up my decision.

#### 7章 線形モデル上のバンディット問題のテスト

「バンディット問題の理論とアルゴリズム」[1] の7章のアルゴリズムを実装して動かしてみる．

#### Bayesian Linear Regression

Lowercase unweighted $x$ means scalar, lowercase bold $\mathbf{x}$ is a vector, and uppercase bold $\mathbf{X}$ is a matrix.

#### Is it Real? Or is it Random?

There is a legend that Professor Burton G. Malkiel, author of A Random Walk Down Wall Street , constructed a price chart by flipping a coin and presented it to a world-renowned chartist to analyze. The chartist studied the movements ...

#### 第3章 一般化線型モデル(GLM) ～ポアソン回帰～

ポアソン回帰 (Poisson regression)$\cdots$個体ごとに異なる説明変数(個体の属性)によって平均種子数が変化する. $\rightarrow$第2章ではどの個体の種子数$y_i$も平均$\lambda$のポアソン分布にしたがうと仮定

#### This website does not host notebooks, it only renders notebooks available on other websites.

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#### Use OSMnx to plot street network over place shape

Notice this municipal boundary is an administrative boundary, not a physical boundary, so it represents jurisdictional bounds, not individiual physical features like islands.

#### Statistical Inference for Everyone: Technical Supplement

The purpose of this supplement is to provide a place where the comparison between the orthodox, frequentist , statistical approach and the current, probability theory as logic , approach is made explicit. It is my contention that all of the ...

#### Kernel matching pursuit (KMP)

This website does not host notebooks, it only renders notebooks available on other websites.

#### Classification

It looks at accuracy, precision, recall, F1, F1 Weighted, and the Matthews Correlation Coefficient (MCC).

#### Sk15

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#### Introducción a la teoría de probabilidad con Python

"En el fondo, la teoría de probabilidades es sólo sentido común expresado con números"

#### P3: OpenStreetMap Data Case Study. Dubai and Abu-Dhabi.

https://www.datacamp.com/community/tutorials/r-data-import-tutorial#gs.jUE2UHw

#### Notes

The red bars and line are are a binned histogram and kernel density estimation of a normal distribution with mean of 5,386 (the actual number of nuts) and standard deviation of 5386/2 (a guesstimation!)

#### A Deep Dive into Geospatial Analysis

In this tutorial we will take a deep dive into geospatial analysis in Python, using tools like geopandas , shapely , and pysal to analyze a dataset, provided by Kaggle (and originally from Inside AirBnB ), of sample AirBnB locations ...

#### Visualization with Matplotlib

The text is released under the CC-BY-NC-ND license , and code is released under the MIT license . If you find this content useful, please support the work by buying the book !

#### 総数 = 1940002

This website does not host notebooks, it only renders notebooks available on other websites.