Software Design in Python - Most Python Projects Fail Because of This Structure

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31.5 hours of video
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data science python data science data science projects data science project python data science project data science project structure data scientist machine learning data visualization data science tutorial data science for beginners data science roadmap

Full Transcript

👷 Review code better and faster with my 3-Factor Framework: https://arjan.codes/diagnosis. In this video, I’ll cover 7 tips to streamline the structure of your Python data science projects. With the right setup and thoughtful software design, you'll be able to modify and enhance your projects more efficiently. Check out Taipy here: https://github.com/avaiga/taipy. Cookiecutter: https://github.com/drivendata/cookiecutter-data-science. 🎓 ArjanCodes Courses: https://www.arjancodes.com/courses. 💬 Join my Discord server: https://discord.arjan.codes. ⌨️ Keyboard I’m using: https://amzn.to/49YM97v. 🔖 Chapters: 0:00 Intro 0:50 Tip #1: Use a common structure 1:55 Tip #2: Use existing libraries 4:59 Tip #3: Log your results 5:55 Tip #4: Use intermediate data representations 8:09 Tip #5: Move reusable code to a shared editable package 9:24 Tip #6: Move configuration to a separate file 11:45 Tip #7: Write unit tests 14:09 Final thoughts #arjancodes #softwaredesign #python

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