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Add super hero classification assignment
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‎.gitattributes

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*.zip filter=lfs diff=lfs merge=lfs -text
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*.enc filter=lfs diff=lfs merge=lfs -text
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*.tar filter=lfs diff=lfs merge=lfs -text

‎autosuggest/superhero-machine-learning-api/LICENSE

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The MIT License (MIT)
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Copyright (c) 2016 Jonas Brunsgaard
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎autosuggest/superhero-machine-learning-api/README.md

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![heroes](/exercise/marvel.png?raw=true "heroes")
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## Build a superhero api with machine learning capabilities
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Dataset and exercise that we use as part of the hiring process for machine
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learning related jobs at e-conomic (Visma).
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From `exercise.tex`;
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> Here at e-conomic we really love superheros. In fact we love superheros
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> so much that we have decided to start a new department which will focus
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> solely on inventing new superhero characters. Our team of dedicated
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> inventors will think out new awesome characters and for each new creation
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> the inventor will devise a character description containing information
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> such as abilities, partnerships, team affiliations, etc.
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>
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> The two legendary US publishers, Marvel Comics and DC Comics, have shown
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> great interest in our new department, and they would like to make offers
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> on each new character....
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>
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> Due to market circumstances, when a new character is offered to a
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> publisher, all other publishers lose interest in buying that character,
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> because they are afraid that the company who got the offer first, may
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> steal the idea and bring onto the market a similar superhero, before the
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> investment can be legally secured.
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>
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> That is why we need your help! We mined Wikipedia for Marvel- and
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> DC-superhero articles, and now we hand you the dataset.
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>
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> Your task is to build a RESTful API that (i) manages the articles, (ii) and
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> offers a prediction endpoint, that uses machine learning to classify a text
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> as being either closer to the Marvel or the DC universe.

‎autosuggest/superhero-machine-learning-api/code/fetch_hero_dataset.py.enc

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‎autosuggest/superhero-machine-learning-api/exercise/dc.jpg

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‎autosuggest/superhero-machine-learning-api/exercise/exercise.tex

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\documentclass{article}
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\usepackage{wrapfig}
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\usepackage{graphicx}
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\usepackage{color}
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\usepackage{enumitem,lipsum}
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\usepackage[labelformat=empty]{caption}
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\linespread{1.05}
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\title{The Superhero Machine Learning Api}
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\date{}
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\begin{document}
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\maketitle
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% \thispagestyle{empty}
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Here at e-conomic we really love superheros. In fact we love superheros
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so much that we have decided to start a new department which will focus
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solely on inventing new superhero characters. Our team of dedicated
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inventors will think out new awesome characters and for each new creation
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the inventor will devise a character description containing information
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such as abilities, partnerships, team affiliations, etc.
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The two legendary US publishers, Marvel Comics and DC Comics, have shown
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great interest in our new department, and they would like to make offers
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on each new character.
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\begin{figure}[h]
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\minipage{0.5\textwidth}
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\centering
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\includegraphics[width=0.7\textwidth]{marvel}
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\caption*{\scriptsize{Superheros published by Marvel Comics}}
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\endminipage\hfill
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\minipage{0.5\textwidth}
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\centering
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\includegraphics[width=0.8\textwidth]{dc}
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\caption*{\scriptsize{Superheros published by DC Comics}}
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\endminipage
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\end{figure}
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Due to market circumstances, when a new character is offered to a
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publisher, all other publishers lose interest in buying that character,
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because they are afraid that the company who got the offer first, may
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steal the idea and bring onto the market a similar superhero, before the
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investment can be legally secured.
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That is why we need your help! We mined Wikipedia for Marvel- and
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DC-superhero articles, and now we hand you the dataset\footnote{In the
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handout you will find \texttt{data.zip}}.
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Your task is to build a RESTful API that (\textit{i}) manages the
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articles, (\textit{ii}) and offers a prediction endpoint, that uses
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machine learning to classify a text as being either closer to the Marvel
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or the DC universe.
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\clearpage
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The API should use some kind of database for persistence and offer the
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following endpoints.
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\vspace{0.5cm}
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\begin{description}[labelindent=0.5cm, leftmargin=1cm]
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\item[\texttt{/article/(\$id)}] \hfill \\
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Article resource endpoint(s). The api should as minimum be able
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to read a resource, creates a resource, updates a resource,
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delete a resource and list resource URI's. The training data from
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\texttt{data.zip} should be posted to this endpoint.
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\item[\texttt{/train}] \hfill \\
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Train or re-train your machine learning model based on the
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articles in the database.
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\item[\texttt{/predict}] \hfill \\
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Receive a text as input and return classification results.
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\end{description}
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\vspace{0.5cm}
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\noindent You will present the solution to a team of e-conomic developers
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and they might have questions and suggestions about the code and machine
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learning techniques. Keep in mind that we do not expect your code to be
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production ready. What we're looking for is how you approach the problem,
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preferably creating some nice and clean code along the way. We will
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appreciate if your solution is working and comes with a build guide, so
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that we can run and test it.
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When presenting the solution you are welcome to bring your own laptop if
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that suits you better. In case you have questions, please do not hesitate
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to ask.
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\\\\
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Happy coding :)
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\end{document}

‎autosuggest/superhero-machine-learning-api/exercise/marvel.png

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