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

Stop wasting hours on bad ML models—learn how Pipelines, feature engineering, and tuning can skyrocket accuracy and automate your machine learning workflow fast.

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

If you are not already subscribed to my premium make sure you do as you get exclusive access to these articles and all my code to follow along with!

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!

👉 If you get value from these podcasts, please help me out, leave it a ❤️, and share it with others. This helps more people discover this podcast! Thank you so much!


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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


👉 If you liked this episode, please leave it a ❤️ and share it with others. This helps more people discover this podcast on Substack, which helps me out and shows me you enjoy content like this! The button is located right below here! ⤵️

Thank you for taking the time to listen to this week’s episode!

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

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