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Coursera - Applied Machine Learning in Python

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  2. File Size：553.44 MB
  3. Creat Time：2024-05-25
  4. Active Degree：16
  5. Last Active：2024-10-13
  6. File Tags：Coursera  Applied  Machine  Learning  in  Python  
  7. Statement：This site does not provide download links, only text displays, and does not contain any infringement.
File List:

    Coursera - Applied Machine Learning in Python

  1. 03_module-3/01_module-3-evaluation/01_model-evaluation-selection.mp4 32.52 MB
  2. 02_module-2/01_module-2-supervised-machine-learning/05_linear-regression-least-squares.mp4 31.04 MB
  3. 02_module-2/01_module-2-supervised-machine-learning/06_linear-regression-ridge-lasso-and-polynomial-regression.mp4 29.99 MB
  4. 02_module-2/01_module-2-supervised-machine-learning/12_decision-trees.mp4 28.15 MB
  5. 04_module-4/01_module-4-supervised-machine-learning-part-2/05_neural-networks.mp4 27.74 MB
  6. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/07_k-nearest-neighbors-classification.mp4 27.55 MB
  7. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/03_key-concepts-in-machine-learning.mp4 24.36 MB
  8. 03_module-3/01_module-3-evaluation/08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.mp4 20.54 MB
  9. 04_module-4/01_module-4-supervised-machine-learning-part-2/08_data-leakage.mp4 19.60 MB
  10. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/05_an-example-machine-learning-problem.mp4 19.56 MB
  11. 02_module-2/01_module-2-supervised-machine-learning/01_introduction-to-supervised-machine-learning.mp4 19.45 MB
  12. 02_module-2/01_module-2-supervised-machine-learning/08_linear-classifiers-support-vector-machines.mp4 18.76 MB
  13. 02_module-2/01_module-2-supervised-machine-learning/04_k-nearest-neighbors-classification-and-regression.mp4 18.24 MB
  14. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/02_introduction.mp4 17.91 MB
  15. 04_module-4/01_module-4-supervised-machine-learning-part-2/03_random-forests.mp4 17.86 MB
  16. 03_module-3/01_module-3-evaluation/05_multi-class-evaluation.mp4 17.12 MB
  17. 02_module-2/01_module-2-supervised-machine-learning/07_logistic-regression.mp4 16.84 MB
  18. 03_module-3/01_module-3-evaluation/02_confusion-matrices-basic-evaluation-metrics.mp4 16.58 MB
  19. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/06_examining-the-data.mp4 16.04 MB
  20. 02_module-2/01_module-2-supervised-machine-learning/02_overfitting-and-underfitting.mp4 15.94 MB
  21. 02_module-2/01_module-2-supervised-machine-learning/11_cross-validation.mp4 13.23 MB
  22. 04_module-4/01_module-4-supervised-machine-learning-part-2/02_naive-bayes-classifiers.mp4 12.59 MB
  23. 02_module-2/01_module-2-supervised-machine-learning/10_kernalized-support-vector-machines.mp4 12.45 MB
  24. 04_module-4/01_module-4-supervised-machine-learning-part-2/06_deep-learning-optional.mp4 11.02 MB
  25. 02_module-2/01_module-2-supervised-machine-learning/09_multi-class-classification.mp4 10.16 MB
  26. 03_module-3/01_module-3-evaluation/03_classifier-decision-functions.mp4 10.14 MB
  27. 03_module-3/01_module-3-evaluation/06_regression-evaluation.mp4 9.88 MB
  28. 04_module-4/01_module-4-supervised-machine-learning-part-2/04_gradient-boosted-decision-trees.mp4 8.72 MB
  29. 03_module-3/01_module-3-evaluation/04_precision-recall-and-roc-curves.mp4 8.29 MB
  30. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/04_python-tools-for-machine-learning.mp4 7.89 MB
  31. 02_module-2/01_module-2-supervised-machine-learning/03_supervised-learning-datasets.mp4 7.45 MB
  32. 04_module-4/01_module-4-supervised-machine-learning-part-2/01_introduction.mp4 4.67 MB
  33. 03_module-3/01_module-3-evaluation/07_practical-guide-to-controlled-experiments-on-the-web.pdf 504 KB
  34. 02_module-2/01_module-2-supervised-machine-learning/13_a-few-useful-things-to-know-about-machine-learning_cacm12.pdf 160 KB
  35. 03_module-3/01_module-3-evaluation/01_model-evaluation-selection.en.srt 30 KB
  36. 02_module-2/01_module-2-supervised-machine-learning/12_decision-trees.en.srt 29 KB
  37. 04_module-4/01_module-4-supervised-machine-learning-part-2/05_neural-networks.en.srt 28 KB
  38. 02_module-2/01_module-2-supervised-machine-learning/05_linear-regression-least-squares.en.srt 28 KB
  39. 02_module-2/01_module-2-supervised-machine-learning/06_linear-regression-ridge-lasso-and-polynomial-regression.en.srt 27 KB
  40. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/07_k-nearest-neighbors-classification.en.srt 26 KB
  41. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/03_key-concepts-in-machine-learning.en.srt 19 KB
  42. 03_module-3/01_module-3-evaluation/08_model-selection-optimizing-classifiers-for-different-evaluation-metrics.en.srt 18 KB
  43. 02_module-2/01_module-2-supervised-machine-learning/07_logistic-regression.en.srt 17 KB
  44. 02_module-2/01_module-2-supervised-machine-learning/04_k-nearest-neighbors-classification-and-regression.en.srt 17 KB
  45. 02_module-2/01_module-2-supervised-machine-learning/01_introduction-to-supervised-machine-learning.en.srt 17 KB
  46. 04_module-4/01_module-4-supervised-machine-learning-part-2/03_random-forests.en.srt 17 KB
  47. 04_module-4/01_module-4-supervised-machine-learning-part-2/08_data-leakage.en.srt 17 KB
  48. 01_module-1/01_module-1-fundamentals-of-machine-learning-intro-to-scikit-learn/02_introduction.en.srt 16 KB
  49. 03_module-3/01_module-3-evaluation/02_confusion-matrices-basic-evaluation-metrics.en.srt 16 KB
  50. 02_module-2/01_module-2-supervised-machine-learning/02_overfitting-and-underfitting.en.srt 16 KB
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