Watch Machine Learning with Python! Train, Test, Split for Evaluating Models Video Tutorial


Tutorial Details & Info

Tutorial Title: Machine Learning with Python! Train, Test, Split for Evaluating Models
Instructor / Channel: Adrian Dolinay
Lesson Runtime: 34:46 Minutes
Publish Date: May 20, 2022
Total Students / Views: 4,271 views

Explore this free video tutorial for Machine Learning with Python! Train, Test, Split for Evaluating Models presented by Adrian Dolinay. This full video course has a total duration of 34:46 minutes providing step-by-step visual instructions. Watch this video tutorial for free without any subscription or sign-up required.

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Course Description & Lesson Notes

Official Video Description:

Tutorial on how to split training and testing data using Python. Learn about the difference between training and testing data sets, create a train_test_split function from scratch and find the optimal proportion to allocate to a training data set. Link to Mean Squared Error Tutorial: https://www.youtube.com/watch?v=tJpzKILW-Kg GitHub repo containing the notebook under "Machine Learning with Python" - https://github.com/ad17171717/YouTube-Tutorials CONNECT: LinkedIn: https://www.linkedin.com/in/adrian-dolinay-frm-96a289106/ GitHub: https://github.com/ad17171717 Twitter: https://twitter.com/DolinayG Odysee: https://odysee.com/@adriandolinay:0 Medium: https://medium.com/@adriandolinay |-Video Chapters-| 0:00 - Intro 0:17 - Definition of training/testing data sets and data splitting 2:03 - Overview of data set 3:34 - Reading data into a pandas DataFrame 4:36 - Graphing the data 5:53 - Creating a train_test_split function from scratch 15:45 - Testing our train_test_split function against Scikit-learn's function 16:52 - Using random forest to model GPU prices 17:30 - Overfitting a model 23:20 - Underfitting a model 25:59 - Finding the optimal proportion to allocate to a training data set 33:42 - References and additional learning

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Explore how to apply Machine Learning With Python! Train, Test, Split For Evaluating Models with this step-by-step video tutorial guide. Throughout this course, you will discover practical tips for Machine Learning With Python! Train, Test, Split For Evaluating Models.

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Machine Learning with Python! Train, Test, Split for Evaluating Models taught by Adrian Dolinay. This tutorial provides a comprehensive walkthrough designed to take you from foundational principles to practical implementation.

💡 Key Topics Covered in This Course:

  • Core Fundamentals & Setup: Understanding the workspace, essential tools, and initial setup for Machine Learning with Python! Train, Test, Split for Evaluating Models.
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by Adrian Dolinay with real-world examples.
  • Best Practices & Key Shortcuts: Time-saving workflows, keyboard shortcuts, and industry-standard recommendations.
  • Troubleshooting & Common Pitfalls: How to avoid common beginner errors and optimize your workflow for peak efficiency.

📋 Recommended Prerequisites & Study Notes:

No prior advanced experience is required. Follow along with the video player above on any desktop computer, tablet, or mobile device. Pause and rewind at key steps to practice along with the instructor.

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