:orphan:


.. _l-notebooks:

Notebook Gallery
================



:ref:`l-notebooks-coverage`


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    :depth: 1
    :local:


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API REST
--------

A few notebooks on REST API.

.. contents::
    :local:
    :depth: 1



.. toctree::
    :maxdepth: 1

    notebooks/rest_api_search_images

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    <div class="sphx-pyq-thumb" tooltip="This example starts a waitress server, creates a WSGI application based on falcon and queries the REST API. This application takes an image and searches for similar images based on features produced by a deep learning model.">

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    .. figure:: /notebooks/rest_api_search_images.thumb.png

        :ref:`restapisearchimagesrst`

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    </div>

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Challenges
----------

The following notebook introduce materials, explanation for challenge
about algorithmic or data.


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    :depth: 1




Guess working and living areas in a city
++++++++++++++++++++++++++++++++++++++++

Shared bicycles are available in almost every big city around the world.
The data about available bicycles or trips are usually open.
These notebooks show some ways to collect and use this data.



.. toctree::
    :maxdepth: 1

    notebooks/city_bike_solution_cluster
    notebooks/city_bike_solution_cluster_start
    notebooks/bike_chicago
    notebooks/business_chicago
    notebooks/city_bike_challenge
    notebooks/city_bike_views
    notebooks/city_bike_solution
    notebooks/bike_seatle

.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="We used a little bit of machine learning on Divvy Data to dig into a better division of Chicago. We try to identify patterns among bike stations.">

.. only:: html

    .. figure:: /notebooks/city_bike_solution_cluster.thumb.png

        :ref:`citybikesolutionclusterrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="We used a little bit of machine learning on Divvy Data to dig into a better division of Chicago. We try to identify patterns among bike stations.">

.. only:: html

    .. figure:: /notebooks/city_bike_solution_cluster_start.thumb.png

        :ref:`citybikesolutionclusterstartrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="This notebooks displays some of the data available at Divvy Data. We assume the data was downloaded.">

.. only:: html

    .. figure:: /notebooks/bike_chicago.thumb.png

        :ref:`bikechicagorst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="This notebooks displays some of the data available at Business Licenses - Current Active. We assume the data was downloaded.">

.. only:: html

    .. figure:: /notebooks/business_chicago.thumb.png

        :ref:`businesschicagorst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="Based on the data available at Divvy Data, how to guess where people usually live and where the usually work?">

.. only:: html

    .. figure:: /notebooks/city_bike_challenge.thumb.png

        :ref:`citybikechallengerst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Based on the data available at Divvy Data, some ways to look at the data.">

.. only:: html

    .. figure:: /notebooks/city_bike_views.thumb.png

        :ref:`citybikeviewsrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Based on the data available at Divvy Data, how to guess where people usually live and where the usually work? This notebook suggests some directions and shows some results.">

.. only:: html

    .. figure:: /notebooks/city_bike_solution.thumb.png

        :ref:`citybikesolutionrst`

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    </div>


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    <div class="sphx-pyq-thumb" tooltip="This notebooks displays some of the data available at Pronto Open Data. We assume the data was downloaded.">

.. only:: html

    .. figure:: /notebooks/bike_seatle.thumb.png

        :ref:`bikeseatlerst`

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    </div>

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Optimize a route
++++++++++++++++

What is the shortest path going through a set of streets in a city?
You will find some tips about the answer among the following notebook.


.. toctree::
    :maxdepth: 1

    notebooks/city_tour_long
    notebooks/city_tour_long_solution
    notebooks/city_tour_1
    notebooks/city_tour_1_solution
    notebooks/city_tour_data_preparation

.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Bigger examples for the challenge: find the shortest path through a set of streets.">

.. only:: html

    .. figure:: /notebooks/city_tour_long.thumb.png

        :ref:`citytourlongrst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="Solutions to the bigger examples for the challenge: find the shortest path through a set of streets.">

.. only:: html

    .. figure:: /notebooks/city_tour_long_solution.thumb.png

        :ref:`citytourlongsolutionrst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="This notebooks introduces an algorithmic challenge which consists in finding the shortest path through a set of streets. It gives examples and functions to test a solution.">

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    .. figure:: /notebooks/city_tour_1.thumb.png

        :ref:`citytour1rst`

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    </div>


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    <div class="sphx-pyq-thumb" tooltip="Find the shortest path through a set of streets, solution of the first example.">

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    .. figure:: /notebooks/city_tour_1_solution.thumb.png

        :ref:`citytour1solutionrst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="Preparation of the examples for the challenge: find the shortest path through a set of streets.">

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    .. figure:: /notebooks/city_tour_data_preparation.thumb.png

        :ref:`citytourdatapreparationrst`

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    </div>

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k-Nearest Neighbours and Sparse features
++++++++++++++++++++++++++++++++++++++++

This a kind of mathematical puzzle which happens in 
a machine learning problem. Thatt riddle shows why sometimes
it is quite helpful to understand a little bit of the mathematics
behind the scenes.


.. toctree::
    :maxdepth: 1

    notebooks/nearest_neighbours_sparse_features

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    <div class="sphx-pyq-thumb" tooltip="While trying to apply k-nearest neighbours classifier database, we might face a tricky issue. Let's try to find out what it is, why it is happening and how to solve it.">

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    .. figure:: /notebooks/nearest_neighbours_sparse_features.thumb.png

        :ref:`nearestneighbourssparsefeaturesrst`

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    </div>

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Trajectoires de vélib
+++++++++++++++++++++

Le système :epkg:`vélib` permet de connaître l'état
des stations à intervalles réguliers. Ces données permettent-elles
d'estimer la vitesse moyenne des cyclistes utilisant ce moyen 
de locomotion ? Que peut-on imaginer pour calculer un estimateur
de cette vitesse ?



.. toctree::
    :maxdepth: 1

    notebooks/velib_trajectories

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    <div class="sphx-pyq-thumb" tooltip="Ce notebook explicite une solution pour calculer la vitesse moyenne des velib sachant qu'on ne connaît que l'état des stations à intervalle réguliers.">

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    .. figure:: /notebooks/velib_trajectories.thumb.png

        :ref:`velibtrajectoriesrst`

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    </div>

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Cheat Sheets
------------


Tips, tricks, tweaks about anything.


.. toctree::
    :maxdepth: 1

    notebooks/chsh_graphs
    notebooks/chsh_html
    notebooks/chsh_dates
    notebooks/chsh_files
    notebooks/chsh_geo
    notebooks/image_features
    notebooks/chsh_images
    notebooks/chsh_pip_install
    notebooks/chsh_pandas

.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Links, pointers on many plotting libraries.">

.. only:: html

    .. figure:: /notebooks/chsh_graphs.thumb.png

        :ref:`chshgraphsrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Parse HTML and extract information.">

.. only:: html

    .. figure:: /notebooks/chsh_html.thumb.png

        :ref:`chshhtmlrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Cheat sheet on dates.">

.. only:: html

    .. figure:: /notebooks/chsh_dates.thumb.png

        :ref:`chshdatesrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Cheat sheet on files.">

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    .. figure:: /notebooks/chsh_files.thumb.png

        :ref:`chshfilesrst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="Cheat sheet on geocoding.">

.. only:: html

    .. figure:: /notebooks/chsh_geo.thumb.png

        :ref:`chshgeorst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Read an image with opencv.">

.. only:: html

    .. figure:: /notebooks/image_features.thumb.png

        :ref:`imagefeaturesrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Cheat sheet how to converge image into arrays and the other way around.">

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    .. figure:: /notebooks/chsh_images.thumb.png

        :ref:`chshimagesrst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="How to install a module from a notebook.">

.. only:: html

    .. figure:: /notebooks/chsh_pip_install.thumb.png

        :ref:`chshpipinstallrst`

.. raw:: html

    </div>


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    <div class="sphx-pyq-thumb" tooltip="Cheat sheet on uncommand operation with pandas such as reading a big file.">

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    .. figure:: /notebooks/chsh_pandas.thumb.png

        :ref:`chshpandasrst`

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    </div>

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   <div style='clear:both'></div>


Coding Problems
---------------

Enigma, coding problems, exercises pour interviews...

.. contents::
    :local:
    :depth: 1



.. toctree::
    :maxdepth: 1

    notebooks/dices_sequence

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    <div class="sphx-pyq-thumb" tooltip="Ce problème est issu de Google Jam : Dice Straight (2017). On dispose de *N* dès à six faces sur lesquelles sont écrits six nombres entiers quelconques. On cerche ) former une séquence de dés de telle sorte que deux dés consécutifs montre deux nombres entiers qui se ssuivent. Quel est la longueur de la plus grande séquence de dès qui vérifient ces contraintes ?">

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    .. figure:: /notebooks/dices_sequence.thumb.png

        :ref:`dicessequencerst`

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    </div>

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hackathon_2015
--------------

.. toctree::
    :maxdepth: 1

    notebooks/process_clean_files
    notebooks/database_schemas
    notebooks/download_data_azure
    notebooks/times_series
    notebooks/upload_donnees

.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / Red Cross / 2015. Cleaning the data, change encoding.">

.. only:: html

    .. figure:: /notebooks/process_clean_files.thumb.png

        :ref:`processcleanfilesrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / Red Cross / 2015. Schema of the databases.">

.. only:: html

    .. figure:: /notebooks/database_schemas.thumb.png

        :ref:`databaseschemasrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / Red Cross / 2015. Connect to an Azure blob storage.">

.. only:: html

    .. figure:: /notebooks/download_data_azure.thumb.png

        :ref:`downloaddataazurerst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / Red Cross / 2015. Extract and plot a time series.">

.. only:: html

    .. figure:: /notebooks/times_series.thumb.png

        :ref:`timesseriesrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / Red Cross / 2015. Upload data to a blob storage.">

.. only:: html

    .. figure:: /notebooks/upload_donnees.thumb.png

        :ref:`uploaddonneesrst`

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    </div>

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Materials for the ENSAE Hackathon 2018
--------------------------------------

See more about this hackathon at :ref:`l-hackathon-2018`.

.. toctree::
    :maxdepth: 1

    notebooks/donnees_insee
    notebooks/baseline_images_keras
    notebooks/images_dups
    notebooks/images_gets

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    <div class="sphx-pyq-thumb" tooltip="Prétraitement des données IRIS.">

.. only:: html

    .. figure:: /notebooks/donnees_insee.thumb.png

        :ref:`donneesinseerst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Petit exemple appris sur très peu d'images...">

.. only:: html

    .. figure:: /notebooks/baseline_images_keras.thumb.png

        :ref:`baselineimageskerasrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / BRGM / 2018. Les images sont extraites de tweets mais sont retweetées sans être retweetées.">

.. only:: html

    .. figure:: /notebooks/images_dups.thumb.png

        :ref:`imagesdupsrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Material for the hackathon ENSAE / BRGM / 2018. Les images sont extraites de tweets mais sont retweetées sans être retweetées.">

.. only:: html

    .. figure:: /notebooks/images_gets.thumb.png

        :ref:`imagesgetsrst`

.. raw:: html

    </div>

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   <div style='clear:both'></div>


hackathon_2022
--------------

.. toctree::
    :maxdepth: 1

    notebooks/traitement_du_son

.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="Quelques éléments de code pour le hackathon 2022.">

.. only:: html

    .. figure:: /notebooks/traitement_du_son.thumb.png

        :ref:`traitementdusonrst`

.. raw:: html

    </div>

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   <div style='clear:both'></div>


Premier pas en machine learning
-------------------------------

Quelques idées simples pour démarrer avec des données.

.. contents::
    :local:
    :depth: 1



.. toctree::
    :maxdepth: 1

    notebooks/online_news_popylarity
    notebooks/PCA

.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="This notebook suggests a couple of ways to explore the data of a machine learning problem.">

.. only:: html

    .. figure:: /notebooks/online_news_popylarity.thumb.png

        :ref:`onlinenewspopylarityrst`

.. raw:: html

    </div>


.. raw:: html

    <div class="sphx-pyq-thumb" tooltip="This notebook shows how to plot a PCA with sciki-learn and statsmodels, with or without normalization.">

.. only:: html

    .. figure:: /notebooks/PCA.thumb.png

        :ref:`PCArst`

.. raw:: html

    </div>




.. toctree::
    :hidden: 

    all_notebooks_coverage