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Links to the best IPython and Jupyter Notebooks.

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Introduction

Introduction

Sending/receiving tables and images over SAMP — Astropy v1.3.2

Isle of Wight Local Elections

Isle of Wight Local Elections

Reusing code and ideas from:

BART ridership between stops

BART ridership between stops

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

Scikit-learn Classification Algorithms

Scikit-learn Classification Algorithms

Classification is concerned with building a model that separates data into distinct classes. This model is built by inputting a set of training data for which the classes are prelabeled in order for the algorithm to learn from. The model ...

How to train your DragoNN tutorial

How to train your DragoNN tutorial

In this tutorial, we will:

Preface

Preface

Introductory textbook for Kalman filters and Bayesian filters. The book is written using Jupyter Notebook so you may read the book in your browser and also run and modify the code, seeing the results inside the book. What better way ...

Playing around with NLTK

Playing around with NLTK

For the linguistics concepts used here, refer to the specific notebook .

Set Twitter and MonkeyLearn API credentials

Set Twitter and MonkeyLearn API credentials

You can signup with MonkeyLearn and get your API token .

Your first neural network

Your first neural network

A critical step in working with neural networks is preparing the data correctly. Variables on different scales make it difficult for the network to efficiently learn the correct weights. Below, we've written the code to load and prepare the data. ...

Scikit-learn Classification Algorithms

Scikit-learn Classification Algorithms

Classification is concerned with building a model that separates data into distinct classes. This model is built by inputting a set of training data for which the classes are prelabeled in order for the algorithm to learn from. The model ...

Gumbel Softmax / Concrete VAE with BayesFlow

Gumbel Softmax / Concrete VAE with BayesFlow

17 Feb 2017

Introduction

Introduction

We load the MNIST data and reshape it into the 2D arrays.

Scikit-learn Classification Algorithms

Scikit-learn Classification Algorithms

Classification is concerned with building a model that separates data into distinct classes. This model is built by inputting a set of training data for which the classes are prelabeled in order for the algorithm to learn from. The model ...

IPython Kernel

IPython Kernel

IPython provides extensions to the Python programming language that make working interactively convenient and efficient. These extensions are implemented in the IPython Kernel and are available in all of the IPython Frontends (Notebook, Terminal, Console and Qt Console) when running ...

Streaming results from keras to plot.ly

Streaming results from keras to plot.ly

This then serves as a small guide to how I achieved what I needed for my purposes. In a nutshell, I used the callbacks functions in Keras to initialize a streaming connection plot.ly , and then at the end of ...

KMR (Kandori-Mailath-Rob)モデルのシミュレーション

KMR (Kandori-Mailath-Rob)モデルのシミュレーション

利得表は

Appendix F - Introduction to NumPy

Appendix F - Introduction to NumPy

Other code examples and content are available on GitHub . The PDF and ebook versions of the book are available through Leanpub .

Pytorch Cheatsheet

Pytorch Cheatsheet

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

Appendix F - Introduction to NumPy

Appendix F - Introduction to NumPy

Other code examples and content are available on GitHub . The PDF and ebook versions of the book are available through Leanpub .

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

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

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Pytorch Cheatsheet

Pytorch Cheatsheet

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

Beltway reporters

Beltway reporters

The goal is to determine a start date for limiting dataset.

A Simple Autoencoder

A Simple Autoencoder

In this notebook, we'll be build a simple network architecture for the encoder and decoder. Let's get started by importing our libraries and getting the dataset.

Risky Domains

Risky Domains

This notebook explores the modeling of risky domains where the usage of the term risky has the dual characteristics of being both 'not common' and 'associated with bad'.

Convolutional Autoencoder

Convolutional Autoencoder

The encoder part of the network will be a typical convolutional pyramid. Each convolutional layer will be followed by a max-pooling layer to reduce the dimensions of the layers. The decoder though might be something new to you. The decoder ...

1章 Python 入門

1章 Python 入門

※補足:整数除算は // 演算子が利用できる。

Layer1

Layer1

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Construction jobs analysis

Construction jobs analysis

The Los Angeles Times conducted an analysis of federal data to evaluate the makeup and pay of construction work.

Playing around with the linear perceptron algorithm

Playing around with the linear perceptron algorithm

Now, let generate a collection of points and then paint them according to a line. If the points are above the line, they are blue, if they are below, green.

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

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

Delivered by Fastly , Rendered by Rackspace