Notebook Gallery

Links to the best IPython and Jupyter Notebooks.

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The Goal

The Goal

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

Motivation:

Motivation:

-- Correlation and covariance matrices are input parameters for a wide variety of financial models

Tutorial 104: Time Series Basics with Pandas and Finance Data

Tutorial 104: Time Series Basics with Pandas and Finance Data

This tutorial will introduce the use of the Cognitive Toolkit for time series data. We show how to prepare time series data for deep learning algorithms. We will cover training a neural network and evaluating the neural network model. We ...

TensorBoard

TensorBoard

A webpage version of this tutorial is available at http://edwardlib.org/tutorials/tensorboard .

Reparameterization Trick

Reparameterization Trick

Assume we have a normal distribution $q$ that is parameterized by $\theta$, specifically $q_{\theta}(x) = N(\theta,1)$. We want to solve the below problem $$ \text{min}_{\theta} \quad E_q[x^2] $$ This is of course a rather silly problem and the optimal $\theta$ ...

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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Introduction

Introduction

This notebook was originally designed as an adjunct to a talk I gave at CSUMB introducing neural networks.

Gridded t-SNE image visualization

Gridded t-SNE image visualization

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Vortex

Vortex

a source-sink pair —you learned how to make a streamplot() and use scatter() to mark the location of the singular points. If you did your challenge task, you saw that equipotential lines are perpendicular to streamlines.

Modeling and Simulation in Python

Modeling and Simulation in Python

Copyright 2017 Allen Downey

Here i will show how you can use Plumed built in CV module to implement the middle latent space of ...

Here i will show how you can use Plumed built in CV module to implement the middle latent space of ...

Both of these operations can be evaluated using the matheval library inside Plumed (skip to the end if you want the actual code)

Poems analysis

Poems analysis

Requirements:

Relevamiento de carga de datos sospechosa en las elecciones de Provincia de Buenos Aires

Relevamiento de carga de datos sospechosa en las elecciones de Provincia de Buenos Aires

Para esto realicé un programa que obtiene los datos digitalizados de cada una de las mesas y los estructuré en una base de datos para hacer agregaciones y consultas.

Fun with Word Embeddings

Fun with Word Embeddings

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

Naive Gaussian Elimination

Naive Gaussian Elimination

Suppose we have, $$ x + y = 3 $$ $$ 3x - 4y = 2 $$ by subtracting 3 times the first equation from the second equation $$ x + y = 3$$ $$ - 7y = - y ...

Examining the similarity of NCAA rankings systems

Examining the similarity of NCAA rankings systems

Let's first download the csv, as derived from the composite rankings on Massey's site:

Relevamiento de carga de datos sospechosa en las elecciones de Provincia de Buenos Aires

Relevamiento de carga de datos sospechosa en las elecciones de Provincia de Buenos Aires

Para esto realicé un programa que obtiene los datos digitalizados de cada una de las mesas y los estructuré en una base de datos para hacer agregaciones y consultas.

Equity Option Implied Volatility Analytics with Python

Equity Option Implied Volatility Analytics with Python

Python has become an increasingly important tool in the domain of quantitative and algorithmic trading and research. Users range from senior quantitative analysts and researchings pricing complex derivatives using numerical techniques all the way to the retail trader just getting ...

Exploratory Data Analysis of Craft Beers: Data Profiling

Exploratory Data Analysis of Craft Beers: Data Profiling

[More information](https://github.com/rasbt/watermark) about the `watermark` magic command extension.

Attempt to explain regression predictions

Attempt to explain regression predictions

Ultimately we need to trust our model and everything it is built on.

How to use Pandas Groupby-Transform duet

How to use Pandas Groupby-Transform duet

Here we are creating a dummy dataframe. We assume that a customer can have n orders, an order can have m items, and each item can be ordered x times

Factorization Machines with tensorflow tutorial

Factorization Machines with tensorflow tutorial

Blog post by Gabriele Modena: Factorization Machines with Tensorflow

Coin

Coin

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はじめてのNNabla

はじめてのNNabla

データを作成します。

Population Genetics in an RNA World

Population Genetics in an RNA World

So where do we get a population from? As you may have discussed in previous workshops, there are very large datasets containing sequencing information from different populations. So we could download one of these datasets and perform some analysis on ...

Examining the similarity of NCAA rankings systems

Examining the similarity of NCAA rankings systems

Let's first download the csv, as derived from the composite rankings on Massey's site:

Face Generation

Face Generation

You'll be using two datasets in this project:

LSTM (Long Short Term Memory)

LSTM (Long Short Term Memory)

This is an illustration from http://colah.github.io/posts/2015-08-Understanding-LSTMs/ (A highly recommended read)

Overview

Overview

TensorFlow gets its name from tensors , which are arrays of arbitrary dimensionality. A vector is a 1-d array and is known as a 1st-order tensor. A matrix is a 2-d array and a 2nd-order tensor. The "flow" part of ...

Tensor wrangling with TensorFlow

Tensor wrangling with TensorFlow

Softmax function, or normalized exponential function can be used to represent a categorical distribution, i.e. for probability computation in probability theory.