How You Can Use Open Source Materials to Learn Python & Data Science - EuroPython 2018
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The document by Kamila Stępniowska discusses the use of open source materials for learning Python and data science, highlighting the resources available for both beginners and professionals. It emphasizes the importance of community support, practical projects, and contributions to the open source ecosystem to enhance the learning experience. Key topics include data preparation, algorithm selection, and the various tools and platforms available for Python in the data science field.
How You Can Use Open Source Materials to Learn Python & Data Science - EuroPython 2018
- 1. How You Can Use Open Source Materials to Learn Python & Data Science Kamila Stępniowska, EuroPython 2018 github.com/KStepniowska/EuroPython2018 CC-BY
- 2. What can you expect? - Sociology - Diversity: Geek Girls Carrots, Women Who Code, She’s Coding - New Business Manager @10Clouds Please don’t ask me about: 1. How can you become a data scientist in 3 weeks? 2. Which algorithm will solve an “A” or “B” problem? EuroPython 2018 Kamila Stępniowska, CC-BY
- 3. I hope that you will learn more about... RESOURCES - Python and Data Science github.com/KStepniowska/EuroPython2018 Open Source - basics Data Science Workflow PROJECTS & COOPERATION & CONTRIBUTION EuroPython 2018 Kamila Stępniowska, CC-BY
- 4. Shall we? EuroPython 2018 Kamila Stępniowska, CC-BY Fernando José Ignacio Gárate Parra https://bit.ly/2A5MoOW CC BY-NC 2.0
- 5. Open Source EuroPython 2018 Kamila Stępniowska, CC-BY
- 6. “Open data and content can be freely used, modified, and shared by anyone for any purpose” https://opendefinition.org/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 7. Educational Materials Text, Pictures, Videos, Audio Records... https://creativecommons.org/licenses/ EuroPython 2018 Kamila Stępniowska, CC-BY As a User
- 8. Code https://opensource.org/licenses https://www.gnu.org/graphics/license-logos.en.html EuroPython 2018 Kamila Stępniowska, CC-BY As a User
- 9. Pick yours General: choosealicense.com Text: creativecommons.org/licenses/ Code: opensource.org/licenses EuroPython 2018 Kamila Stępniowska, CC-BY As a Creator
- 10. Python EuroPython 2018 Kamila Stępniowska, CC-BY
- 11. Why Python? COMMUNITY Welcoming & Supportive Global & Diverse ... If there is a problem, there is a great chance that someone has written and shared the solution already. EuroPython 2018 Kamila Stępniowska, CC-BY
- 12. Learning Experience Find Your Project -> learn by building Find Your People -> Cooperate Find a way to Contribute -> help others https://bugs.python.org/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 13. For Beginners PEP 8 python.org/dev/peps/pep-0008/ “PEP 8 — the Style Guide for Python Code This stylized presentation of the well-established PEP 8 was created by Kenneth Reitz (for humans).” *PEP=Python Enhancement Proposal pep8.org/#fn1 EuroPython 2018 Kamila Stępniowska, CC-BY
- 14. For Beginners PEP 20 - The Zen of Python python.org/dev/peps/pep-0020/ ... EuroPython 2018 Kamila Stępniowska, CC-BY
- 15. Resources: For Beginners Python, Programming, Open Source Knowledge: python.org -> Beginner’s Guide for Non-Programmers https://bit.ly/1Iv5glG for Programmers https://bit.ly/1UIBJMJ How to learn: Lynn Rooth “Sink or swim” http://www.roguelynn.com/words/The-New-Coder-A-path-to-Software-Engineering/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 16. xkcd CC BY-NC 2.5 https://xkcd.com/1838/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 17. Data Science EuroPython 2018 Kamila Stępniowska, CC-BY
- 18. Use of Python in Data Science Python Developer - Survey 2017 Results (9,500 developers, 150 countries) “What do you use Python for? (multiple answers)” 50% Data analysis, 31% Machine learning jetbrains.com/research/python-developers-survey-2017/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 19. jetbrains.com/research/python-developers-survey-2017/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 20. Python & Data Science - what’s more? Jupiter Notebook jupyter.org/ PyCharm jetbrains.com/pycharm/ Spyder pythonhosted.org/spyder/ EuroPython 2018 Kamila Stępniowska, CC-BY
- 21. Use Python to build your tools to explore data You need to know Python to be able to freely build experiments. EuroPython 2018 Kamila Stępniowska, CC-BY
- 22. “Data” Gathering, cleaning and data preparation is crucial. Typical issues: - there is not enough data - data is messy - we actually don’t know what is in the data set... Gill Press, Forbes https://bit.ly/2OgNM4D EuroPython 2018 Kamila Stępniowska, CC-BY Data preparation is even 80% of a Data Scientist Work
- 23. “Science” - on the hunt for the right questions ● Understand what I want to achieve ● Define the problem that I want to solve ● Define what is the input and what I want to be an output ● Looking for helpful algorithms ● Compare the chosen algorithms ● Choose the algorithm/s to be used ● Choose the evaluation metrics ● Choose parameters set for experiments ● Run experiments ● Analyse the results ● Define the conclusions and/or get back to previous points Anna Gut, Python Developer & Team Lead @10Clouds EuroPython 2018 Kamila Stępniowska, CC-BY UNDERSTAND SEARCH EXPERIMENT
- 24. How to find the right algorithm? The Internet… - the resource - do you define the source as trusted? (eg. scikit-learn) - number of stars, forks, when was the last commit? (GitHub) - the code - is it aligned with the Python standards? (PEP 8) - check the particular functions - ... - does it fit to the general architecture of a project? - ask a friend Anna Gut, Python Developer & Team Lead @10Clouds EuroPython 2018 Kamila Stępniowska, CC-BY
- 25. Hacks - what was your steps & how did you get there Step is a wrapper over the transformer and handles multiple aspects of the execution of the pipeline, such as saving intermediate results (if needed), checkpointing the model during training and more. Transformer is purely computational, data scientist-defined piece that takes an input data and produces some output data. Typical Transformers are neural network, machine learning algorithms and pre- or post-processing routines. github.com/neptune-ml/steppy EuroPython 2018 Kamila Stępniowska, CC-BY
- 26. Resources Data Science, Open Source All… datasciencemasters.org/ Transformation from Math & Phys into Data Science: p.migdal.pl/2016/03/15/data-science-intro-for-math-phys-background.html EuroPython 2018 Kamila Stępniowska, CC-BY
- 27. Projects Cooperation Contribution EuroPython 2018 Kamila Stępniowska, CC-BY
- 28. Projects Find your project - newcoder.io/tutorials/ - www.kaggle.com/ - devmesh.intel.com/ EuroPython 2018 Kamila Stępniowska, CC-BY POSSIBLE? DRIVING ME?
- 29. Cooperation Online: - pyslackers.com (14,757 members) - mail.python.org/mailman/listinfo/tutor - https://www.facebook.com/groups/python.programmers Offline: - PyData, PyWaw - PyLadies, Girl Geek, Geek Girls Carrots (Krakow) - Django Carrots, Django Girls EuroPython 2018 Kamila Stępniowska, CC-BY
- 30. Contribution - Bag Tracker bugs.python.org - Open Source Projects opensource.guide/how-to-contribute - Answer questions at pyslackers.com - Become a speaker/mentor pydata.org - Organize Django Girls djangogirls.org/organize - ... EuroPython 2018 Kamila Stępniowska, CC-BY
- 31. Even More Resources... EuroPython 2018 Kamila Stępniowska, CC-BY
- 32. Open Education jose.theoj.org EuroPython 2018 Kamila Stępniowska, CC-BY
- 33. Thank you! EuroPython 2018 Kamila Stępniowska, CC-BY github.com/KStepniowska/EuroPython2018 kamila.stepniowska@10clouds.com @kstepniowska