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[ CourseLala.com ] Skillshare - Machine Learning, Neural Networks, Computer Vision, Deep Learning and Reinforcement
magnet:?xt=urn:btih:66b444c43bcbda144557c74c2a5e781642dded52&dn=[ CourseLala.com ] Skillshare - Machine Learning, Neural Networks, Computer Vision, Deep Learning and Reinforcement
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66b444c43bcbda144557c74c2a5e781642dded52
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71
文件数量
2.33 GB
文件大小
2024-1-26 05:21
创建日期
2024-11-24 08:40
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CourseLala
com
Skillshare
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Machine
Learning
Neural
Networks
Computer
Vision
Deep
Learning
and
Reinforcement
~Get Your Files Here !/01. Introduction.mp4 27.93 MB
~Get Your Files Here !/02. Installing TensorFlow and Keras.mp4 6.23 MB
~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning.mp4 26.6 MB
~Get Your Files Here !/04. Types of artificial intelligence learning.mp4 33.03 MB
~Get Your Files Here !/05. Fundamentals of statistics.mp4 31.12 MB
~Get Your Files Here !/06. What is linear regression.mp4 35.68 MB
~Get Your Files Here !/07. Linear regression theory optimization.mp4 44.38 MB
~Get Your Files Here !/08. Linear regression theory gradient descent.mp4 35 MB
~Get Your Files Here !/09. Linear regression implementation I.mp4 87.21 MB
~Get Your Files Here !/10. Linear regression implementation II.mp4 19.37 MB
~Get Your Files Here !/11. What is logistic regression.mp4 38.17 MB
~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation.mp4 24.78 MB
~Get Your Files Here !/13. Logistic regression example I sigmoid function.mp4 47.32 MB
~Get Your Files Here !/14. Logistic regression example II credit scoring.mp4 66.5 MB
~Get Your Files Here !/15. What is cross validation.mp4 26.48 MB
~Get Your Files Here !/16. Cross validation example.mp4 26.1 MB
~Get Your Files Here !/17. What is the k nearest neighbor classifier.mp4 16.67 MB
~Get Your Files Here !/18. Concept of lazy learning.mp4 18.57 MB
~Get Your Files Here !/19. Distance metrics Euclidean distance.mp4 20.79 MB
~Get Your Files Here !/20. Bias and variance trade off.mp4 15.65 MB
~Get Your Files Here !/21. K nearest neighbor implementation I.mp4 31.4 MB
~Get Your Files Here !/22. K nearest neighbor implementation II.mp4 50.28 MB
~Get Your Files Here !/23. K nearest neighbor implementation III.mp4 23.87 MB
~Get Your Files Here !/24. What is the naive Bayes classifier.mp4 46.88 MB
~Get Your Files Here !/25. Naive Bayes classifier illustration.mp4 9.69 MB
~Get Your Files Here !/26. Naive Bayes classifier implementation.mp4 17.51 MB
~Get Your Files Here !/27. What is text clustering.mp4 75.13 MB
~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF).mp4 28.06 MB
~Get Your Files Here !/29. Naive Bayes example clustering news.mp4 90.44 MB
~Get Your Files Here !/30. What are Support Vector Machines (SVMs).mp4 21.27 MB
~Get Your Files Here !/31. Linearly separable problems.mp4 34.56 MB
~Get Your Files Here !/32. Non linearly separable problems.mp4 24.8 MB
~Get Your Files Here !/33. Kernel functions.mp4 31.05 MB
~Get Your Files Here !/34. Support vector machine example I simple.mp4 47.9 MB
~Get Your Files Here !/35. Support vector machine example II iris dataset.mp4 32.35 MB
~Get Your Files Here !/36. Support vector machines example III parameter tuning.mp4 41.6 MB
~Get Your Files Here !/37. Support vector machine example IV digit recognition.mp4 42.81 MB
~Get Your Files Here !/38. Support vector machine example V digit recognition.mp4 30.46 MB
~Get Your Files Here !/39. Advantages and disadvantages.mp4 7.25 MB
~Get Your Files Here !/40. Decision trees introduction basics.mp4 29.36 MB
~Get Your Files Here !/41. Decision trees introduction entropy.mp4 40.5 MB
~Get Your Files Here !/42. Decision trees introduction information gain.mp4 37.84 MB
~Get Your Files Here !/43. The Gini index approach.mp4 32.21 MB
~Get Your Files Here !/44. Decision trees introduction pros and cons.mp4 9.16 MB
~Get Your Files Here !/45. Decision trees implementation I.mp4 29.56 MB
~Get Your Files Here !/46. Decision trees implementation II parameter tuning.mp4 24.18 MB
~Get Your Files Here !/47. Decision tree implementation III identifying cancer.mp4 30.33 MB
~Get Your Files Here !/48. Pruning introduction.mp4 20.26 MB
~Get Your Files Here !/49. Bagging introduction.mp4 28.19 MB
~Get Your Files Here !/50. Random forest classifier introduction.mp4 20.81 MB
~Get Your Files Here !/51. Random forests example I iris dataset.mp4 21.29 MB
~Get Your Files Here !/52. Random forests example II credit scoring.mp4 14.47 MB
~Get Your Files Here !/53. Random forests example III OCR parameter tuning.mp4 63.16 MB
~Get Your Files Here !/54. Boosting introduction basics.mp4 19.44 MB
~Get Your Files Here !/55. Boosting introduction illustration.mp4 15.46 MB
~Get Your Files Here !/56. Boosting introduction equations.mp4 21.71 MB
~Get Your Files Here !/57. Boosting introduction final formula.mp4 45.88 MB
~Get Your Files Here !/58. Boosting implementation I iris dataset.mp4 30.59 MB
~Get Your Files Here !/59. Boosting implementation II wine classification.mp4 76.66 MB
~Get Your Files Here !/60. Boosting vs bagging.mp4 14.36 MB
~Get Your Files Here !/61. Principal component analysis (PCA) introduction.mp4 38.65 MB
~Get Your Files Here !/62. Principal component analysis example.mp4 49.95 MB
~Get Your Files Here !/63. Principal component analysis example II.mp4 46.33 MB
~Get Your Files Here !/64. K means clustering introduction.mp4 27.96 MB
~Get Your Files Here !/65. K means clustering example.mp4 36.89 MB
~Get Your Files Here !/66. K means clustering text clustering.mp4 65.81 MB
~Get Your Files Here !/67. DBSCAN introduction.mp4 16.78 MB
~Get Your Files Here !/68. DBSCAN example.mp4 42.34 MB
~Get Your Files Here !/69. Hierarchical clustering introduction.mp4 17.45 MB
~Get Your Files Here !/70. Hierarchical clustering example.mp4 36.55 MB
~Get Your Files Here !/71. 008 Hierarchical clustering market segmentation.mp4 46.5 MB
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