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<!doctype html>
<html lang="it">
<head>
<meta charset="utf-8">
<title>Python Toolkit</title>
<meta name="viewport" content="width=device-width, initial-scale=1.0, maximum-scale=1.0, user-scalable=no">
<link rel="stylesheet" href="dist/reveal.css">
<link rel="stylesheet" href="dist/theme/shetech.css" id="theme">
<link rel="stylesheet" href="plugin/highlight/monokai.css">
</head>
<body>
<div id="brand"><a class="brand_img" href="https://shetechitaly.org/" target="_blank" rel="noopener noreferrer"><img
src="img/shetech-logo.png" alt="Logo SheTech" width="50" height="50"></a> <a class="brand_img"
href="https://www.docebo.com/" target="_blank" rel="noopener noreferrer"><img
src="img/docebo-logo-vector.svg" alt="Logo Docebo" width="100" height="22"></a> </div>
<div class="reveal">
<div class="slides">
<section>
<img src="img/python-karate.svg" alt="Logo Python" id="python_karate">
<h3>Python e Machine Learning</h3>
<p class="intro">Hai partecipato al bootcamp di sabato<br>e vuoi diventare cintura nera di pandas e sklearn?<br>
Ecco i link ai materiali del bootcamp e altre risorse per proseguire.</p>
<div><button class="intro_btn" onclick="Reveal.slide(1, 0)">Bootcamp</button><button class="intro_btn"
onclick="Reveal.slide(2, 0)">Risorse</button></div>
<p class="notes">Usa barra spaziatrice e frecce per navigare</p>
</section>
<section>
<section class="content">
<h2 id="python_title">Bootcamp</h2>
<p class="intro">I link ai materiali visti durante il bootcamp di sabato</p>
</section>
<section>
<!-- <h3 class="slide_title">Python Crash Course</h3> -->
<p>
<a href="https://colab.research.google.com/drive/11o-hmuI9MYxPwhc_nw-b22KIIto18AS8" target="_blank"
rel="noopener noreferrer"><img src="img/Python-crash-course-ipynb-Colaboratory.png" alt="schermata Colab"
class="img_website"></a>
</p>
<p>Il <a href="https://colab.research.google.com/drive/11o-hmuI9MYxPwhc_nw-b22KIIto18AS8" target="_blank" rel="noopener noreferrer">notebook con gli esercizi di Python</a> per imparare le basi di questo linuaggio.</p>
</section>
<section>
<!-- <h3 class="slide_title">Introduzione al Machine Learning</h3> -->
<p>
<a href="https://docs.google.com/presentation/d/1nkgXgpcBSg6GAjxpqE9XM1sPBCH7gyjR4S7JspTEPzA/edit#slide=id.g597410d81a_0_5" target="_blank"
rel="noopener noreferrer"><img src="img/ml_map.jpg" alt="schermata slide"
class="img_website"></a>
</p>
<p>Le <a href="https://docs.google.com/presentation/d/1nkgXgpcBSg6GAjxpqE9XM1sPBCH7gyjR4S7JspTEPzA/edit#slide=id.g597410d81a_0_5" target="_blank" rel="noopener noreferrer">slide per orientarsi fra processi e algoritmi</a> del Machine Learning.</p>
</section>
<section>
<!-- <h3 class="slide_title">ML sezna soluzioni</h3> -->
<p>
<a href="https://colab.research.google.com/drive/16FlZYfDIYy_fQ8Llv7skyj0WdsgSSAPN?usp=sharing#scrollTo=fTb0-fI4a6nx" target="_blank"
rel="noopener noreferrer"><img src="img/Bootcamp-ML-ipynb-Colaboratory.jpg" alt="schermata Colab"
class="img_website"></a>
</p>
<p>I due <a href="https://colab.research.google.com/drive/16FlZYfDIYy_fQ8Llv7skyj0WdsgSSAPN?usp=sharing#scrollTo=fTb0-fI4a6nx" target="_blank" rel="noopener noreferrer">esercizi di Machine Learning</a> per allenare i tuoi primi modelli (senza soluzioni).</p>
</section>
<section>
<!-- <h3 class="slide_title">ML sezna soluzioni</h3> -->
<p>
<a href="https://colab.research.google.com/drive/1RNBQqDT13zbSHiRfjdq8T8mCTqS5v89n?usp=sharing" target="_blank"
rel="noopener noreferrer"><img src="img/Soluzione-Bootcamp-ML-ipynb-Colaboratory.png" alt="schermata Colab"
class="img_website"></a>
</p>
<p>I due <a href="https://colab.research.google.com/drive/1RNBQqDT13zbSHiRfjdq8T8mCTqS5v89n?usp=sharing" target="_blank" rel="noopener noreferrer">esercizi di Machine Learning</a> con le soluzioni.</p>
</section>
</section><!-- END FIRST STEPS SECTION -->
<section>
<section>
<h2>📝 Risorse utili</h2>
<p class="intro">Una selezione di risorse per approfondire Python e il Machine Learning</p>
</section>
<section>
<p>
<a href="https://automatetheboringstuff.com/"
target="_blank" rel="noopener noreferrer"><img
src="img/sito-Automate-the-Boring-Stuff-with-Python.png"
alt="copertina libro Automate the Boring Stuff with Python" class="img_website"></a>
</p>
<p><a href="https://automatetheboringstuff.com/"
target="_blank" rel="noopener noreferrer">Automate the Boring Stuff with Python</a> - Per la parte python pura: vi insegna python e un sacco di progetti carini e molto pratici.
</p>
</section>
<section>
<!-- <h3>ML for Beginners</h3> -->
<p>
<a href="https://github.com/microsoft/ML-For-Beginners/blob/main/README.md" target="_blank"
rel="noopener noreferrer"><img src="img/sito-ML-For-Beginners.png"
alt="schermata sito ML for Beginners" class="img_website"></a>
</p>
<p><a href="https://github.com/microsoft/ML-For-Beginners/blob/main/README.md" target="_blank"
rel="noopener noreferrer">Machine Learning for Beginners - A Curriculum</a> - Corso di Microsoft di Machine Learning pensato per "beginners".</p>
</section>
<section>
<p>
<a href="https://www.google.it/books/edition/_/HnetDwAAQBAJ?hl=en&gbpv=0" target="_blank"
rel="noopener noreferrer"><img src="img/cover-Hands-On-Machine-Learning.png"
alt="libro Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow" class="img_website"></a>
</p>
<p><a href="https://www.google.it/books/edition/_/HnetDwAAQBAJ?hl=en&gbpv=0" target="_blank"
rel="noopener noreferrer">Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow</a> - Se preferite i libri, questo è scritto molto bene con parte sia teorica che pratica. Gli esercizi sono <a href="https://github.com/ageron/handson-ml2" target="_blank" rel="noopener noreferrer">disponibili anche online</a>.</p>
</section>
<section>
<p>
<a href="http://themlbook.com/" target="_blank"
rel="noopener noreferrer"><img src="img/sito-The-Hundred-Page-Machine-Learning-Book.png"
alt="libro The hundred page machine learning book" class="img_website"></a>
</p>
<p><a href="http://themlbook.com/" target="_blank"
rel="noopener noreferrer">The Hundred Page Machine Learning Book</a> - Sempre parlando di libri, per la parte teorica scritto molto bene e disponibile anche gratuitamente.</p>
</section>
<section>
<!-- <h3 id="pythoncheatsheet_title" class="slide_title">Python for Data Science</h3> -->
<p>
<a href="https://www.edx.org/course/python-for-data-science-2?index=product&queryID=142d7f5fcf9c2622c5801380d3490ca6&position=1"
target="_blank" rel="noopener noreferrer"><img
src="img/sito-Python-for-Data-Science-edX.png"
alt="schermata sito edX Python for Data Science" class="img_website"></a>
</p>
<p><a href="https://www.edx.org/course/python-for-data-science-2?index=product&queryID=142d7f5fcf9c2622c5801380d3490ca6&position=1"
target="_blank" rel="noopener noreferrer">UC San Diego Python for Data Science</a> - Un mooc
per imparare a utilizzare potenti strumenti Python open-source come Pandas, Git e Matplotlib e per
manipolare, analizzare e visualizzare set di dati complessi.
</p>
</section>
<section>
<!-- <h3 id="pythoncheatsheet_title" class="slide_title">Pythoncheatsheet.org</h3> -->
<p>
<a href="https://www.pythoncheatsheet.org/" target="_blank" rel="noopener noreferrer"><img
src="img/sito-PythonCheatsheet.png" alt="schermata sito Pythoncheatsheet.org"
class="img_website"></a>
</p>
<p><a href="https://www.pythoncheatsheet.org/" target="_blank"
rel="noopener noreferrer">Pythoncheatsheet.org</a> - Sito rivolto a sviluppatori
principianti e avanzati, con l'obiettivo di abbassare la barriera di ingresso per i nuovi
arrivati e fornire un supporto anche ai veterani del codice.
</p>
</section>
<section>
<!-- <h3 id="pwp_title" class="slide_title">Programming with Python</h3> -->
<p>
<a href="https://swcarpentry.github.io/python-novice-inflammation/" target="_blank"
rel="noopener noreferrer"><img src="img/sito-Programming-with-Python.png"
alt="schermata sito Programming with Python" class="img_website"></a>
</p>
<p> <a href="https://swcarpentry.github.io/python-novice-inflammation/" target="_blank"
rel="noopener noreferrer">Programming with Python</a> - Il modo migliore per imparare a
programmare è fare qualcosa di utile, quindi questa introduzione a Python è costruita attorno a
dei task di
analisi dei dati.</p>
</section>
<section>
<!-- <h3 id="hackinscience_title" class="slide_title">Hackinscience</h3> -->
<p>
<a href="https://www.hackinscience.org/" target="_blank" rel="noopener noreferrer"><img
src="img/sito-HackInScience.png" alt="schermata sito HackInScience.png"
class="img_website"></a>
</p>
<p><a href="https://www.hackinscience.org/" target="_blank"
rel="noopener noreferrer">Hackinscience</a> - Una piattaforma di esercizi Python
interattiva: scrivi il codice e ottieni un feedback istantaneo dal bot di correzione con
informazioni dettagliate sugli eventuali errori.</p>
</section>
<section>
<!-- <h3>Python Cheat Sheet</h3> -->
<p>
<a href="https://github.com/ehmatthes/pcc/blob/master/cheat_sheets/" target="_blank"
rel="noopener noreferrer"><img src="img/sito-python-crash-course.png" alt="preview pdf"
class="img_website"></a>
</p>
<p>
<a href="https://github.com/ehmatthes/pcc/blob/master/cheat_sheets/" target="_blank"
rel="noopener noreferrer">Python Cheat Sheets</a> - Questo set di cheat sheet ti aiuterà a
ricordare i concetti base così come la sintassi. Fanno parte del libro <a
href="https://nostarch.com/pythoncrashcourse2e" target="_blank"
rel="noopener noreferrer">Python Crash Course</a>
</p>
</section>
<section>
<!-- <h3 id="eduopen_title" class="slide_title">Eduopen</h3> -->
<p>
<a href="https://learn.eduopen.org/eduopenv2/course_details.php?courseid=194" target="_blank"
rel="noopener noreferrer"><img src="img/sito-eduopen.jpg" alt="schermata sito Eduopen"
class="img_website"></a>
</p>
<p>Il corso online in lingua italiana di <a
href="https://learn.eduopen.org/eduopenv2/course_details.php?courseid=194" target="_blank"
rel="noopener noreferrer">Introduzione alla programmazione con Python</a>
dell'Università di Genova e il pathway in <a
href="https://learn.eduopen.org/eduopenv2/pathway_details.php?specialid=57" target="_blank"
rel="noopener noreferrer">Calcolo Scientifico in Python</a> dell'Università di Padova</p>
</section>
<section>
<!-- <h3>Machine Learning Playground</h3> -->
<p>
<a href="https://mlplaygrounds.com/" target="_blank" rel="noopener noreferrer"><img
src="img/sito-ML-Playground.png" alt="schermata sito Machine Learning Playground"
class="img_website"></a>
</p>
<p><a href="https://mlplaygrounds.com/" target="_blank" rel="noopener noreferrer">Machine Learning
Playground</a> - Una piattaforma per giocare, esplorare e comprendere
diversi algoritmi di Machine Learning.</p>
</section>
<section>
<!-- <h3>UC Irvine ML Repository</h3> -->
<p>
<a href="https://archive.ics.uci.edu/ml/index.php" target="_blank"
rel="noopener noreferrer"><img src="img/sito-UCI-Machine-Learning-Repository.png"
alt="schermata sito UC Irvine ML Repository" class="img_website"></a>
</p>
<p> <a href="https://archive.ics.uci.edu/ml/index.php" target="_blank" rel="noopener noreferrer">UC
Irvine Machine Learning Repository</a> - Un sito con più di 500 dataset su cui potersi
esercitare con le tecniche di Machine Learning.</p>
</section>
<section>
<!-- <h3>ML Specialization</h3> -->
<p>
<a href="https://www.coursera.org/specializations/machine-learning" target="_blank"
rel="noopener noreferrer"><img src="img/sito-Machine-Learning-Coursera.png"
alt="schermata sito Coursera Machine Learning Specialization" class="img_website"></a>
</p>
<p> <a href="https://www.coursera.org/specializations/machine-learning" target="_blank"
rel="noopener noreferrer">University of Washington Machine Learning Specialization</a> - Una
specializzazione che, attraverso una serie di casi di studio pratici, permette di acquisire
esperienza applicativa nelle principali aree dell'apprendimento automatico, tra cui previsione,
classificazione, clustering e recupero delle informazioni.</p>
</section>
<section>
<!-- <h3>#aiadventures</h3> -->
<p>
<a href="https://www.youtube.com/hashtag/aiadventures" target="_blank"
rel="noopener noreferrer"><img src="img/sito-aiadventures.jpg"
alt="schermata sito #aiadventures" class="img_website"></a>
</p>
<p><a href="https://www.youtube.com/hashtag/aiadventures" target="_blank"
rel="noopener noreferrer">#aiadventures</a> - Un canale video che esplora l'arte, la scienza
e gli strumenti del Machine Learning.</p>
</section>
<section>
<!-- <h3 id="aigoogle_title" class="slide_title">Google Ai Education</h3> -->
<p>
<a href="https://ai.google/education/" target="_blank" rel="noopener noreferrer"><img
src="img/sito-Google-AI.jpg" alt="schermata sito Google Ai Education"
class="img_website"></a>
</p>
<p><a href="https://ai.google/education/" target="_blank" rel="noopener noreferrer">Google Ai
Education</a> - Informazioni, tool, dataset ed esercizi per aiutarti a sviluppare le tue
abilità e far avanzare i tuoi progetti.</p>
</section>
<section>
<!-- <h3 id="aigoogle_title" class="slide_title">Udemy</h3> -->
<p>
<a href="https://www.udemy.com/course/data-science-con-python/" target="_blank"
rel="noopener noreferrer"><img src="img/sito-Python-Udemy.png"
alt="schermata sito Udemy Corso" class="img_website"></a>
</p>
<p><a href="https://www.udemy.com/course/data-science-con-python/" target="_blank"
rel="noopener noreferrer">Udemy Corso completo di Data Science e Machine Learning con
Python</a> - Corso in lingua italiana per diventare da principiante a esperto nelle tecniche
di Data Science con Python.</p>
</section>
<section>
<!-- <h3 id="aigoogle_title" class="slide_title">Kaggle tutorial</h3> -->
<p>
<a href="https://www.kaggle.com/learn" target="_blank" rel="noopener noreferrer"><img
src="img/sito-Kaggle.png" alt="schermata sito Kaggle" class="img_website"></a>
</p>
<p><a href="https://www.kaggle.com/learn" target="_blank" rel="noopener noreferrer">Kaggle </a> -
Una serie di tutorial che riducono gli argomenti complessi alle loro componenti pratiche chiave.
</p>
</section>
</section><!-- END TIPS SECTION -->
<section>
<!-- <h4>Strumenti utili per sabato</h4> -->
<p>
<img src="img/giphy-3.gif" alt="basket meme" class="img_website">
</p>
<p>
👂 Ehi, ti aspettiamo anche sui nostri canali Discord e Slack per continuare il percorso insieme
</p>
</section>
<section>
<h4>Credits</h4>
<p class="credits">
<a href="https://www.python.org/" target="_blank" rel="noopener noreferrer">python.org</a><br/>
<a href="https://www.gnu.org/licenses/gpl-3.0.en.html" target="_blank" rel="noopener noreferrer">GPL</a> <br/>
<a href="https://commons.wikimedia.org/w/index.php?curid=34991651" target="_blank" rel="noopener noreferrer">commons.wikimedia.org</a><br/>
<a href="https://revealjs.com/" target="_blank" rel="noopener noreferrer">Reveal.js</a><br>
<a href="https://emojipedia.org/" rel="noopener noreferrer">Emojipedia</a> <br>
<a href="https://www.seekpng.com/" target="_blank" rel="noopener noreferrer">Seekpng</a>
</p>
</section>
</div>
</div>
<script src="dist/reveal.js"></script>
<script>
Reveal.initialize({
history: true,
transition: 'linear',
});
</script>
</body>
</html>