In this comprehensive tutorial, we dive into the world of model validation using cross-validation techniques with Python and Scikit-Learn. Cross-validation plays a pivotal role in assessing the true performance of machine learning models, helping us build robust and reliable solutions.
Interested in discussing a Data or AI project? Feel free to reach out via email or simply complete the contact form on my website.
📧 Email: ryannolandata@gmail.com
🌐 Website & Blog: https://ryannolandata.com/
🍿 WATCH NEXT
Scikit-Learn and Machine Learning Playlist: https://www.youtube.com/playlist?list=PLcQVY5V2UY4LNmObS0gqNVyNdVfXnHwu8
Column Transformer: https://youtu.be/yBLNbeKbFKI
Cross Validation: https://youtu.be/glLNo1ZnmPA
Feature Scaling: https://youtu.be/6eJHk8JYK2M
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👨💻 LinkedIn: https://www.linkedin.com/in/ryan-p-nolan/
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⚙️ GitHub: https://github.com/RyanNolanData
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📚 *Data and AI Courses: https://datacamp.pxf.io/XYD7Qg
📚 *Practice SQL & Python Interview Questions: https://stratascratch.com/?via=ryan
WHO AM I?
As a full-time data analyst/scientist at a fintech company specializing in combating fraud within underwriting and risk, I've transitioned from my background in Electrical Engineering to pursue my true passion: data. In this dynamic field, I've discovered a profound interest in leveraging data analytics to address complex challenges in the financial sector.
This YouTube channel serves as both a platform for sharing knowledge and a personal journey of continuous learning. With a commitment to growth, I aim to expand my skill set by publishing 2 to 3 new videos each week, delving into various aspects of data analytics/science and Artificial Intelligence. Join me on this exciting journey as we explore the endless possibilities of data together.
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