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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8">
<title>PyData London Tutorial Notebooks</title>
</head>
<body>
<h1>Pydata Beginners' Bootcamp</h1>
<hr>
<h3>Github Repo</h3>
<p>Our <a href="https://github.com/conradho/pydata-beginner-bootcamp">Github repo</a> includes this page, a README.md, all the notebooks, and more.</p>
<h3>Notebooks</h3>
<ul>
<li>Data Visualization Notebook (<a href="/pydata/DataVisualization.html">html</a>, <a href="/pydata/DataVisualization.ipynb">ipynb</a>): the least challenging notebook if you don't know where to start from</li>
<li>Geospatial Notebook (<a href="/pydata/Geography.html">html</a>, <a href="/pydata/Geography.ipynb">ipynb</a>): Longitude/Latitude coordinates, nearest neighbors, and map visualizations</li>
<li>Quantitative Finance Notebook (<a href="/pydata/QuantFinance.html">html</a>, <a href="/pydata/QuantFinance.ipynb">ipynb</a>): an investigation into optimal sizing</li>
<li>Natural Language Processing Notebook (<a href="/pydata/NLP.html">html</a>, <a href="/pydata/NLP.ipynb">ipynb</a>): Twitter word count + clusters, sentiment analysis, and a Shakespeare generator </li>
</ul>
<p>Html files include sample output; ipynb files are stripped of output.</p>
<p>For the ipynb files, right click and "save as"- if you click into the link and save the page, then you may get a html version of the .ipynb file, which jupyter won't recognize as a valid ipynb file.</p>
<h3>Other files</h3>
<ul>
<li><a href="http://blog.pythonanywhere.com/127/">another quant finance example</a></li>
<li><a href="/pydata/clean_london_stations_data.py">clean_london_stations_data.py</a></li>
<li><a href="/pydata/process_twitter_stream.py">process_twitter_stream.py</a></li>
<li><a href="/pydata/save_twitter_stream.py">save_twitter_stream.py</a></li>
<li><a href="/pydata/datasets">most of the datasets</a></li>
</ul>
<hr>
<h3>Miscellaneous</h3>
<ul>
<li><a href="/pydata/schedule.html">Today's schedule</a></li>
<li><a href="https://docs.google.com/spreadsheets/d/1aYjO_05PELlTOvTA0Mq1KN8RjJ91o7ARYoDplMeWBGs/edit?usp=sharing">PythonAnywhere account logins tracker</a></li>
<li><a href="https://join.slack.com/t/pydata2018-bootcamp/shared_invite/enQtMzUzNzkzNDkxMjIxLTljZmIzMjA3ZDllOWQ3NjVmNzhiYzNjNGFhNzIwNmM3MzEzOTMwNDhlOTVkOWE1NGZmNGE1YjY4Yzk3YmQxMWQ">Join this slack channel</a> for Bootcamp specific announcements- includes lightning talk slides</li>
<li><a href="https://pydatalondon.herokuapp.com">Click here</a> to join the PyData London slack channel</li>
<li>Confused about which ML algorithm to use? <a href="http://scikit-learn.org/stable/tutorial/machine_learning_map/">Here's a handy chart</a></li>
<li>Free <a href="http://archive.ics.uci.edu/ml/">ML data sets</a></li>
<li>If you have any suggestions, please visit <a href="https://github.com/conradho/pydata-beginner-bootcamp">our Github repo</a>, read the guidelines, and submit a pull request!</li>
</ul>
<hr>
<a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/"><img alt="Creative Commons License" style="border-width:0" src="https://i.creativecommons.org/l/by-sa/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="http://creativecommons.org/licenses/by-sa/4.0/">Creative Commons Attribution-ShareAlike 4.0 International License</a>.
</body>
</html>