Watch Machine Learning: Testing and Error Metrics Video Tutorial


Tutorial Details & Info

Tutorial Title: Machine Learning: Testing and Error Metrics
Instructor / Channel: Luis Serrano Academy
Lesson Runtime: 44:43 Minutes
Publish Date: March 16, 2017
Total Students / Views: 118,076 views

Follow step-by-step with Machine Learning: Testing and Error Metrics presented by Luis Serrano Academy. The total lesson runtime is 44:43 minutes with detailed practical demonstrations. Access this full online lesson on any desktop PC, Mac, tablet, or smartphone.

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Course Description & Lesson Notes

Official Video Description:

Announcement: New Book by Luis Serrano! Grokking Machine Learning. bit.ly/grokkingML 40% discount code: serranoyt A friendly journey into the process of evaluating and improving machine learning models. - Training, Testing - Evaluation Metrics: Accuracy, Precision, Recall, F1 Score - Types of Errors: Overfitting and Underfitting - Cross Validation and K-fold Cross Validation - Model Evaluation Graphs - Grid Search For a code implementation, check out this repo: https://github.com/luisguiserrano/manning/tree/master/Chapter_4_Testing_Overfitting_Underfitting 0:00 Introduction 0:37 Which model is better 1:31 Why Testing? 3:27 Golden Rule # 1 4:21 How do we not 'lose' the training data? 4:38 K-Fold Cross Validation 5:20 Randomizing in Cross Validation 5:38 Evaluation Metrics 7:53 Medical Model 8:05 Spam Classifier Model 9:25 Confusion Matrix Diagnosis 11:50 Accuracy 19:47 Precision and Recall 20:54 Credit Card Fraud 22:36 Harmonic mean 24:08 F1 Score 27:16 Types of Errors 27:56 Classification 30:03 Error due to variance (overfitting) 30:18 Error due to bias (underfitting) 31:45 Tradeoff 37:55 Solution: Cross Validation Testing 39:16 Training a Logistic Regression Model 40:04 Training a Decision Tree 40:49 Training a Support Vector Machine 41:14 Grid Search Cross Validation 41:59 Parameters and Hyperparameters 42:56 How to solve a problem 43:20 How to use machine learning 44:04 Thank you!

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Master how to apply Machine Learning: Testing And Error Metrics with this in-depth video tutorial guide. Throughout this course, you will discover practical tips for Machine Learning: Testing And Error Metrics.

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🎓 Lesson Overview & Learning Outcomes:

Welcome to the step-by-step video guide for Machine Learning: Testing and Error Metrics taught by Luis Serrano Academy. 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: Testing and Error Metrics.
  • Step-by-Step Practical Demonstration: Hands-on implementation guided by Luis Serrano Academy 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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