Demystifying Machine Learning Models: From Random Forests to Neural Networks
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Demystifying Machine Learning Models: From Random Forests to Neural Networks
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About this listen
Welcome to the Kodey Podcast! In today’s episode, we’re unpacking the essentials of some of the most widely used machine learning models—Random Forests, Gradient Boosted Machines, XGBoost, Support Vector Machines, K-Nearest Neighbors, and Neural Networks. We’ll walk through each model with real-life analogies, highlighting what makes each method unique, how they’re used in data science, and how they build on one another. Whether you’re diving into machine learning or brushing up on the basics, this guide offers an intuitive look at how these models work and when to use them
Podcast intro music; https://transistor.fm/free-podcast-intro-music/
This episode contains material generated by ChatGPT, a product of OpenAI
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