Tutorial: CLASSIFICATION TREES in Python

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Codificando Bits

Published on Premiered Nov 11, 2024
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????????Decision Trees Course: https://codificandobits.com/curso/arb... ???????? ????????Personalized advice and training: https://codificandobits.com/servicios ???????? In this tutorial we will see in a practical way how to train and test a classification tree using Python and the Scikit-Learn library. The dataset and notebook for this tutorial: https://drive.google.com/drive/folder... Content: 00:00 Introduction 00:59 Online Academy and Services 01:27 Organization of the tutorial 02:01 Brief review of classification trees 04:37 The problem to be solved and the dataset 16:04 Training and visualization of a tree 26:58 Effect of hyperparameters on the performance of the tree 43:35 Generation of predictions 44:37 Conclusion ???? ** VISIT WWW.CODIFICANDOBITS.COM ** On the website you will find the Online Academy with courses, projects and tutorials that will help you build your career in Artificial Intelligence, Data Science and Machine Learning. ???? ** RECOMMENDED VIDEOS AND PLAYLISTS ** ???? What is a Classification Tree and how does it work?: • Classification with Decision Trees... ???? What is cross-validation (k-fold cross-validation): • Cross-validation and k-fold cross-valida... ???? Cross-validation tutorial: • Tutorial: CROSS-VALIDATION with Scik... ???? ** JOIN CODIFICAANDO BITS AND FOLLOW ME ON MY SOCIAL NETWORKS ** ✅ Website: https://www.codificandobits.com ✅ Subscribe: https://www.youtube.com/c/codificando... ✅ Facebook: /codificandobits ???? ** ABOUT ME ** I am Miguel Sotaquirá, the creator of Codificando Bits. I have a background as an Electronic Engineer, and a PhD in Bioengineering, and since 2017 I have become passionate about Machine Learning and Data Science, and currently I am fully dedicated to disseminating content and providing advice to people and companies on these topics. ???? ** ABOUT CODIFICAANDO BITS ** The goal of Codificando Bits is to inspire and disseminate knowledge in the areas of Machine Learning, Artificial Intelligence and Data Science. #machinelearning

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