get ready to streamline your data transformations! This lecture dives into essential Scikit-learn tools like Pipeline, make_pipeline(), ColumnTransformer, and make_column_selector(). #datascience
Description:
In this comprehensive video lecture, join Prof. Mostafa A. Elhosseini as we delve into the essential world of Transformation Pipelines in Machine Learning. Whether you're a beginner or looking to enhance your skills, this lecture is tailor-made for you! 🌟
What You'll Learn:
Transformation Pipelines: Understand the critical role of transformation pipelines in preprocessing data efficiently and preparing it for model training. 🔄
Pipeline Class: Explore the powerful Pipeline class in Scikit-Learn, which allows for seamless integration and automation of preprocessing steps. ⚙️
make_pipeline() Function: Learn how to create concise and effective pipelines using the make_pipeline() function, making your code cleaner and more readable. ✨
ColumnTransformer: Dive into the ColumnTransformer for applying different transformations to different columns in your dataset, a must-know for handling real-world data. 📊
make_column_selector(): Discover how to select columns by name or datatype automatically using the make_column_selector(), simplifying your preprocessing workflow. 🔍
Join us as we unpack these tools and techniques with practical examples, code demonstrations, and expert insights. Perfect for students, researchers, and professionals keen on elevating their machine learning projects. Don't miss out on unlocking the full potential of your data with transformation pipelines!
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Hashtags: #TransformationPipelines #MachineLearning #DataScience #AI #ProfElhosseiniSmartSysEng #ScikitLearn #DataPreprocessing #TechEdu
#Python #machinelearning 🚀🤖🔬📈
Watch video Lecture 27: Transformation Pipelines Masterclass 🚀- Pipelines, ColumnTransformer, and More! online without registration, duration hours minute second in high quality. This video was added by user ElhosseiniAcademy 17 April 2024, don't forget to share it with your friends and acquaintances, it has been viewed on our site 160 once and liked it 8 people.