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[] data-science-linear-regression-in-python

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  • 文件大小:431MB
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文件列表

  1. 06 Appendix/035 How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow.mp4 44MB
  2. 03 Multiple linear regression and polynomial regression/012 Define the multi-dimensional problem and derive the solution.mp4 36MB
  3. 02 1-D Linear Regression Theory and Code/006 Define the model in 1-D derive the solution.mp4 25MB
  4. 06 Appendix/036 How to Code by Yourself part 1.mp4 25MB
  5. 02 1-D Linear Regression Theory and Code/005 Define the model in 1-D derive the solution Updated Version.mp4 19MB
  6. 02 1-D Linear Regression Theory and Code/010 Demonstrating Moores Law in Code.mp4 17MB
  7. 04 Practical machine learning issues/020 Generalization and Overfitting Demonstration in Code.mp4 17MB
  8. 03 Multiple linear regression and polynomial regression/015 Polynomial regression - extending linear regression with Python code.mp4 16MB
  9. 03 Multiple linear regression and polynomial regression/014 Coding the multi-dimensional solution in Python.mp4 15MB
  10. 06 Appendix/037 How to Code by Yourself part 2.mp4 15MB
  11. 03 Multiple linear regression and polynomial regression/011 Define the multi-dimensional problem and derive the solution Updated Version.mp4 14MB
  12. 02 1-D Linear Regression Theory and Code/007 Coding the 1-D solution in Python.mp4 14MB
  13. 03 Multiple linear regression and polynomial regression/016 Predicting Systolic Blood Pressure from Age and Weight.mp4 12MB
  14. 02 1-D Linear Regression Theory and Code/008 Determine how good the model is - r-squared.mp4 11MB
  15. 04 Practical machine learning issues/017 What do all these letters mean.mp4 10MB
  16. 01 Introduction and Outline/004 How to Succeed in this Course.mp4 9MB
  17. 04 Practical machine learning issues/028 Bypass the Dummy Variable Trap with Gradient Descent.mp4 9MB
  18. 01 Introduction and Outline/002 What is machine learning How does linear regression play a role.mp4 8MB
  19. 04 Practical machine learning issues/030 L1 Regularization - Code.mp4 8MB
  20. 04 Practical machine learning issues/021 Categorical inputs.mp4 8MB
  21. 05 Conclusion and Next Steps/032 Brief overview of advanced linear regression and machine learning topics.mp4 8MB
  22. 04 Practical machine learning issues/022 Probabilistic Interpretation of Squared Error.mp4 8MB
  23. 04 Practical machine learning issues/024 L2 Regularization - Code.mp4 8MB
  24. 04 Practical machine learning issues/026 Gradient Descent Tutorial.mp4 8MB
  25. 05 Conclusion and Next Steps/033 Exercises practice and how to get good at this.mp4 7MB
  26. 04 Practical machine learning issues/023 L2 Regularization - Theory.mp4 7MB
  27. 01 Introduction and Outline/001 Introduction and Outline.mp4 6MB
  28. 04 Practical machine learning issues/025 The Dummy Variable Trap.mp4 6MB
  29. 04 Practical machine learning issues/018 Interpreting the Weights.mp4 6MB
  30. 04 Practical machine learning issues/031 L1 vs L2 Regularization.mp4 5MB
  31. 04 Practical machine learning issues/029 L1 Regularization - Theory.mp4 5MB
  32. 02 1-D Linear Regression Theory and Code/009 R-squared in code.mp4 4MB
  33. 01 Introduction and Outline/003 Introduction to Moores Law Problem.mp4 4MB
  34. 04 Practical machine learning issues/019 Generalization error train and test sets.mp4 4MB
  35. 06 Appendix/034 BONUS Where to get Udemy coupons and FREE deep learning material.mp4 4MB
  36. 04 Practical machine learning issues/027 Gradient Descent for Linear Regression.mp4 4MB
  37. 03 Multiple linear regression and polynomial regression/013 How to solve multiple linear regression using only matrices.mp4 3MB
  38. 04 Practical machine learning issues/quizzes/004 One-hot encoding.html 3KB
  39. 03 Multiple linear regression and polynomial regression/quizzes/003 R-squared.html 3KB
  40. 01 Introduction and Outline/quizzes/001 What can linear regression be used for.html 3KB
  41. 02 1-D Linear Regression Theory and Code/quizzes/002 R-squared.html 2KB
  42. Freetutorials.Us.url 119B
  43. [FreeTutorials.Us].txt 75B