FreeCoursesOnline Us Machine-Learning-Essential-Training-Value-Estimations

1. 00 Introduction/001 Welcome.mp46.79MB
2. 00 Introduction/002 What you should know.mp4619.49KB
3. 00 Introduction/003 Using the exercise files.mp41.23MB
4. 00 Introduction/004 Set up the development environment.mp46.87MB
5. 01 What Is Machine Learning and Value Prediction_/001 What is machine learning_.mp44.57MB
6. 01 What Is Machine Learning and Value Prediction_/002 Supervised machine learning for value prediction.mp45.26MB
7. 01 What Is Machine Learning and Value Prediction_/003 Build a simple home value estimator.mp47.01MB
8. 01 What Is Machine Learning and Value Prediction_/004 Find the best weights automatically.mp46.83MB
9. 01 What Is Machine Learning and Value Prediction_/005 Cool uses of value prediction.mp46.64MB
10. 02 An Overview of Building a Machine Learning System/001 Introduction to NumPy, scikit-learn, and pandas.mp42.06MB
11. 02 An Overview of Building a Machine Learning System/002 Think in vectors_ How to work with large data sets efficiently.mp45.66MB
12. 02 An Overview of Building a Machine Learning System/003 The basic workflow for training a supervised machine learning model.mp43.72MB
13. 02 An Overview of Building a Machine Learning System/004 Gradient boosting_ A versatile machine learning algorithm.mp46.12MB
14. 03 Training Data/001 Explore a home value data set.mp48.34MB
15. 03 Training Data/002 Standard conventions for naming training data.mp41.57MB
16. 03 Training Data/003 Decide how much data you need.mp43.84MB
17. 04 Features/001 Feature engineering.mp46.92MB
18. 04 Features/002 Choose the best features for home value prediction.mp48.85MB
19. 04 Features/003 Use as few features as possible_ The curse of dimensionality.mp43.16MB
20. 05 Coding Our System/001 Prepare the features.mp44.97MB
21. 05 Coding Our System/002 Training vs. testing data.mp42.92MB
22. 05 Coding Our System/003 Train the value estimator.mp48.87MB
23. 05 Coding Our System/004 Measure accuracy with mean absolute error.mp44.51MB
24. 06 Improving Our System/001 Overfitting and underfitting.mp44.52MB
25. 06 Improving Our System/002 The brute force solution_ Grid search.mp46.1MB
26. 06 Improving Our System/003 Feature selection.mp46.85MB
27. 07 Using the Estimator in a Real-World Program/001 Predict values for new data.mp47.63MB
28. 07 Using the Estimator in a Real-World Program/002 Retrain the classifier with fresh data.mp43.65MB
29. 08 Conclusion/001 Wrap-up.mp41.43MB