Automate and Optimize Your ML Models: The Power of Pipelines and Feature Engineering | Episode #93

If you’re spending way too much time training machine learning models and not getting the results you want, this episode of PyPod Chronicles is for you.

I’m breaking down a simple but powerful trick that can save you hours and make your models work way better. You’ll learn how to use pipelines, feature engineering, and hyperparameter tuning to automate your workflow, boost accuracy, and get more out of your models with less effort.

This episode will show you exactly how to make your machine learning process faster and more efficient.

Give it a listen and level up your machine learning skills.

👉 Thank you for allowing me to do work I find meaningful. This is my full time job so I hope you will support my work.

I’ve linked the latest episode of Code with Josh below, How to Use *args and **kwargs

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Along with getting access to my current Machine Learning Series, you also get exclusive access to a boat load more content such as monthly Python projects, weekly long form articles, 3 Randoms, & my complete archive!

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The Data Analytics Playbook

After a lot of hard work, I’m excited to launch my very first book, The Data Analytics Playbook—written just for you, my fellow nerds!

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🎬 How to Use *args and **kwargs

Over on Code with Josh ~ HERE

Check out the video and drop a ❤️. This really helps out the channel!

📚 Other Books I’ve Found Helpful:

* Python Crash Course - Here

* Automate the Boring Stuff - Here

* Data Structures and Algorithms in Python - Here

* Python Pocket Reference - Here

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This is my full-time job so I hope you can support my work as we build together!

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