[ CourseLala.com ] Skillshare - Machine Learning, Neural Networks, Computer Vision, Deep Learning and Reinforcement

磁力链接/BT种子名称

[ CourseLala.com ] Skillshare - Machine Learning, Neural Networks, Computer Vision, Deep Learning and Reinforcement

磁力链接/BT种子简介

种子哈希：66b444c43bcbda144557c74c2a5e781642dded52
文件大小： 2.33G
已经下载：981次
下载速度：极快
收录时间：2023-12-31
最近下载：2025-10-10

移花宫入口

移花宫.com邀月.com怜星.com花无缺.comyhgbt.icuyhgbt.top

磁力链接下载

magnet:?xt=urn:btih:66B444C43BCBDA144557C74C2A5E781642DDED52
推荐使用PIKPAK网盘下载资源，10TB超大空间，不限制资源，无限次数离线下载，视频在线观看

下载BT种子文件

磁力链接 迅雷下载 PIKPAK在线播放 世界之窗 91视频 含羞草 欲漫涩 逼哩逼哩 成人快手 51品茶 抖阴破解版 极乐禁地 91短视频 抖音Max TikTok成人版 PornHub 听泉鉴鲍 暗网Xvideo 草榴社区 哆哔涩漫 呦乐园 萝莉岛 悠悠禁区 拔萝卜 疯马秀

最近搜索

文件列表

  • ~Get Your Files Here !/29. Naive Bayes example clustering news.mp4 94.8 MB
  • ~Get Your Files Here !/09. Linear regression implementation I.mp4 91.4 MB
  • ~Get Your Files Here !/59. Boosting implementation II wine classification.mp4 80.4 MB
  • ~Get Your Files Here !/27. What is text clustering.mp4 78.8 MB
  • ~Get Your Files Here !/14. Logistic regression example II credit scoring.mp4 69.7 MB
  • ~Get Your Files Here !/66. K means clustering text clustering.mp4 69.0 MB
  • ~Get Your Files Here !/53. Random forests example III OCR parameter tuning.mp4 66.2 MB
  • ~Get Your Files Here !/22. K nearest neighbor implementation II.mp4 52.7 MB
  • ~Get Your Files Here !/62. Principal component analysis example.mp4 52.4 MB
  • ~Get Your Files Here !/34. Support vector machine example I simple.mp4 50.2 MB
  • ~Get Your Files Here !/13. Logistic regression example I sigmoid function.mp4 49.6 MB
  • ~Get Your Files Here !/24. What is the naive Bayes classifier.mp4 49.2 MB
  • ~Get Your Files Here !/71. 008 Hierarchical clustering market segmentation.mp4 48.8 MB
  • ~Get Your Files Here !/63. Principal component analysis example II.mp4 48.6 MB
  • ~Get Your Files Here !/57. Boosting introduction final formula.mp4 48.1 MB
  • ~Get Your Files Here !/07. Linear regression theory optimization.mp4 46.5 MB
  • ~Get Your Files Here !/37. Support vector machine example IV digit recognition.mp4 44.9 MB
  • ~Get Your Files Here !/68. DBSCAN example.mp4 44.4 MB
  • ~Get Your Files Here !/36. Support vector machines example III parameter tuning.mp4 43.6 MB
  • ~Get Your Files Here !/41. Decision trees introduction entropy.mp4 42.5 MB
  • ~Get Your Files Here !/61. Principal component analysis (PCA) introduction.mp4 40.5 MB
  • ~Get Your Files Here !/11. What is logistic regression.mp4 40.0 MB
  • ~Get Your Files Here !/42. Decision trees introduction information gain.mp4 39.7 MB
  • ~Get Your Files Here !/65. K means clustering example.mp4 38.7 MB
  • ~Get Your Files Here !/70. Hierarchical clustering example.mp4 38.3 MB
  • ~Get Your Files Here !/06. What is linear regression.mp4 37.4 MB
  • ~Get Your Files Here !/08. Linear regression theory gradient descent.mp4 36.7 MB
  • ~Get Your Files Here !/31. Linearly separable problems.mp4 36.2 MB
  • ~Get Your Files Here !/04. Types of artificial intelligence learning.mp4 34.6 MB
  • ~Get Your Files Here !/35. Support vector machine example II iris dataset.mp4 33.9 MB
  • ~Get Your Files Here !/43. The Gini index approach.mp4 33.8 MB
  • ~Get Your Files Here !/21. K nearest neighbor implementation I.mp4 32.9 MB
  • ~Get Your Files Here !/05. Fundamentals of statistics.mp4 32.6 MB
  • ~Get Your Files Here !/33. Kernel functions.mp4 32.6 MB
  • ~Get Your Files Here !/58. Boosting implementation I iris dataset.mp4 32.1 MB
  • ~Get Your Files Here !/38. Support vector machine example V digit recognition.mp4 31.9 MB
  • ~Get Your Files Here !/47. Decision tree implementation III identifying cancer.mp4 31.8 MB
  • ~Get Your Files Here !/45. Decision trees implementation I.mp4 31.0 MB
  • ~Get Your Files Here !/40. Decision trees introduction basics.mp4 30.8 MB
  • ~Get Your Files Here !/49. Bagging introduction.mp4 29.6 MB
  • ~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF).mp4 29.4 MB
  • ~Get Your Files Here !/64. K means clustering introduction.mp4 29.3 MB
  • ~Get Your Files Here !/01. Introduction.mp4 29.3 MB
  • ~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning.mp4 27.9 MB
  • ~Get Your Files Here !/15. What is cross validation.mp4 27.8 MB
  • ~Get Your Files Here !/16. Cross validation example.mp4 27.4 MB
  • ~Get Your Files Here !/32. Non linearly separable problems.mp4 26.0 MB
  • ~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation.mp4 26.0 MB
  • ~Get Your Files Here !/46. Decision trees implementation II parameter tuning.mp4 25.4 MB
  • ~Get Your Files Here !/23. K nearest neighbor implementation III.mp4 25.0 MB
  • ~Get Your Files Here !/56. Boosting introduction equations.mp4 22.8 MB
  • ~Get Your Files Here !/51. Random forests example I iris dataset.mp4 22.3 MB
  • ~Get Your Files Here !/30. What are Support Vector Machines (SVMs).mp4 22.3 MB
  • ~Get Your Files Here !/50. Random forest classifier introduction.mp4 21.8 MB
  • ~Get Your Files Here !/19. Distance metrics Euclidean distance.mp4 21.8 MB
  • ~Get Your Files Here !/48. Pruning introduction.mp4 21.2 MB
  • ~Get Your Files Here !/54. Boosting introduction basics.mp4 20.4 MB
  • ~Get Your Files Here !/10. Linear regression implementation II.mp4 20.3 MB
  • ~Get Your Files Here !/18. Concept of lazy learning.mp4 19.5 MB
  • ~Get Your Files Here !/26. Naive Bayes classifier implementation.mp4 18.4 MB
  • ~Get Your Files Here !/69. Hierarchical clustering introduction.mp4 18.3 MB
  • ~Get Your Files Here !/67. DBSCAN introduction.mp4 17.6 MB
  • ~Get Your Files Here !/17. What is the k nearest neighbor classifier.mp4 17.5 MB
  • ~Get Your Files Here !/20. Bias and variance trade off.mp4 16.4 MB
  • ~Get Your Files Here !/55. Boosting introduction illustration.mp4 16.2 MB
  • ~Get Your Files Here !/52. Random forests example II credit scoring.mp4 15.2 MB
  • ~Get Your Files Here !/60. Boosting vs bagging.mp4 15.1 MB
  • ~Get Your Files Here !/25. Naive Bayes classifier illustration.mp4 10.2 MB
  • ~Get Your Files Here !/44. Decision trees introduction pros and cons.mp4 9.6 MB
  • ~Get Your Files Here !/39. Advantages and disadvantages.mp4 7.6 MB
  • ~Get Your Files Here !/02. Installing TensorFlow and Keras.mp4 6.5 MB
  • ~Get Your Files Here !/09. Linear regression implementation I-fr.vtt 24.2 kB
  • ~Get Your Files Here !/09. Linear regression implementation I-de.vtt 23.7 kB
  • ~Get Your Files Here !/29. Naive Bayes example clustering news-fr.vtt 23.6 kB
  • ~Get Your Files Here !/31. Linearly separable problems-de.vtt 23.3 kB
  • ~Get Your Files Here !/31. Linearly separable problems-fr.vtt 23.1 kB
  • ~Get Your Files Here !/09. Linear regression implementation I-es-MX.vtt 22.9 kB
  • ~Get Your Files Here !/29. Naive Bayes example clustering news-es-MX.vtt 22.9 kB
  • ~Get Your Files Here !/29. Naive Bayes example clustering news-de.vtt 22.8 kB
  • ~Get Your Files Here !/09. Linear regression implementation I-pt.vtt 22.6 kB
  • ~Get Your Files Here !/31. Linearly separable problems-es-MX.vtt 22.5 kB
  • ~Get Your Files Here !/29. Naive Bayes example clustering news-pt.vtt 22.4 kB
  • ~Get Your Files Here !/31. Linearly separable problems-pt.vtt 22.1 kB
  • ~Get Your Files Here !/31. Linearly separable problems-en-US.vtt 21.4 kB
  • ~Get Your Files Here !/09. Linear regression implementation I-en-US.vtt 21.4 kB
  • ~Get Your Files Here !/11. What is logistic regression-de.vtt 21.2 kB
  • ~Get Your Files Here !/29. Naive Bayes example clustering news-en-US.vtt 21.2 kB
  • ~Get Your Files Here !/11. What is logistic regression-fr.vtt 20.9 kB
  • ~Get Your Files Here !/11. What is logistic regression-es-MX.vtt 20.3 kB
  • ~Get Your Files Here !/11. What is logistic regression-pt.vtt 19.8 kB
  • ~Get Your Files Here !/11. What is logistic regression-en-US.vtt 19.0 kB
  • ~Get Your Files Here !/24. What is the naive Bayes classifier-fr.vtt 18.9 kB
  • ~Get Your Files Here !/24. What is the naive Bayes classifier-de.vtt 18.8 kB
  • ~Get Your Files Here !/24. What is the naive Bayes classifier-es-MX.vtt 18.5 kB
  • ~Get Your Files Here !/13. Logistic regression example I sigmoid function-fr.vtt 18.5 kB
  • ~Get Your Files Here !/13. Logistic regression example I sigmoid function-de.vtt 18.3 kB
  • ~Get Your Files Here !/34. Support vector machine example I simple-de.vtt 18.2 kB
  • ~Get Your Files Here !/34. Support vector machine example I simple-fr.vtt 18.2 kB
  • ~Get Your Files Here !/24. What is the naive Bayes classifier-pt.vtt 18.1 kB
  • ~Get Your Files Here !/14. Logistic regression example II credit scoring-fr.vtt 17.8 kB
  • ~Get Your Files Here !/14. Logistic regression example II credit scoring-de.vtt 17.8 kB
  • ~Get Your Files Here !/13. Logistic regression example I sigmoid function-es-MX.vtt 17.7 kB
  • ~Get Your Files Here !/34. Support vector machine example I simple-es-MX.vtt 17.7 kB
  • ~Get Your Files Here !/34. Support vector machine example I simple-pt.vtt 17.6 kB
  • ~Get Your Files Here !/33. Kernel functions-fr.vtt 17.4 kB
  • ~Get Your Files Here !/14. Logistic regression example II credit scoring-es-MX.vtt 17.4 kB
  • ~Get Your Files Here !/13. Logistic regression example I sigmoid function-pt.vtt 17.4 kB
  • ~Get Your Files Here !/14. Logistic regression example II credit scoring-pt.vtt 16.9 kB
  • ~Get Your Files Here !/24. What is the naive Bayes classifier-en-US.vtt 16.9 kB
  • ~Get Your Files Here !/33. Kernel functions-de.vtt 16.9 kB
  • ~Get Your Files Here !/64. K means clustering introduction-en-US.vtt 16.9 kB
  • ~Get Your Files Here !/59. Boosting implementation II wine classification-en-US.vtt 16.9 kB
  • ~Get Your Files Here !/13. Logistic regression example I sigmoid function-en-US.vtt 16.8 kB
  • ~Get Your Files Here !/33. Kernel functions-es-MX.vtt 16.8 kB
  • ~Get Your Files Here !/34. Support vector machine example I simple-en-US.vtt 16.6 kB
  • ~Get Your Files Here !/33. Kernel functions-pt.vtt 16.4 kB
  • ~Get Your Files Here !/37. Support vector machine example IV digit recognition-fr.vtt 16.3 kB
  • ~Get Your Files Here !/62. Principal component analysis example-en-US.vtt 16.2 kB
  • ~Get Your Files Here !/14. Logistic regression example II credit scoring-en-US.vtt 16.2 kB
  • ~Get Your Files Here !/06. What is linear regression-de.vtt 16.1 kB
  • ~Get Your Files Here !/37. Support vector machine example IV digit recognition-es-MX.vtt 16.0 kB
  • ~Get Your Files Here !/06. What is linear regression-fr.vtt 15.9 kB
  • ~Get Your Files Here !/43. The Gini index approach-de.vtt 15.7 kB
  • ~Get Your Files Here !/37. Support vector machine example IV digit recognition-de.vtt 15.6 kB
  • ~Get Your Files Here !/43. The Gini index approach-fr.vtt 15.6 kB
  • ~Get Your Files Here !/37. Support vector machine example IV digit recognition-pt.vtt 15.5 kB
  • ~Get Your Files Here !/06. What is linear regression-es-MX.vtt 15.5 kB
  • ~Get Your Files Here !/33. Kernel functions-en-US.vtt 15.5 kB
  • ~Get Your Files Here !/07. Linear regression theory optimization-fr.vtt 15.3 kB
  • ~Get Your Files Here !/04. Types of artificial intelligence learning-fr.vtt 15.3 kB
  • ~Get Your Files Here !/66. K means clustering text clustering-en-US.vtt 15.3 kB
  • ~Get Your Files Here !/43. The Gini index approach-es-MX.vtt 15.3 kB
  • ~Get Your Files Here !/06. What is linear regression-pt.vtt 15.1 kB
  • ~Get Your Files Here !/53. Random forests example III OCR parameter tuning-en-US.vtt 15.1 kB
  • ~Get Your Files Here !/43. The Gini index approach-pt.vtt 15.1 kB
  • ~Get Your Files Here !/04. Types of artificial intelligence learning-es-MX.vtt 14.9 kB
  • ~Get Your Files Here !/04. Types of artificial intelligence learning-de.vtt 14.9 kB
  • ~Get Your Files Here !/07. Linear regression theory optimization-de.vtt 14.9 kB
  • ~Get Your Files Here !/07. Linear regression theory optimization-es-MX.vtt 14.7 kB
  • ~Get Your Files Here !/71. 008 Hierarchical clustering market segmentation-en-US.vtt 14.7 kB
  • ~Get Your Files Here !/37. Support vector machine example IV digit recognition-en-US.vtt 14.7 kB
  • ~Get Your Files Here !/22. K nearest neighbor implementation II-fr.vtt 14.6 kB
  • ~Get Your Files Here !/06. What is linear regression-en-US.vtt 14.5 kB
  • ~Get Your Files Here !/04. Types of artificial intelligence learning-pt.vtt 14.5 kB
  • ~Get Your Files Here !/22. K nearest neighbor implementation II-de.vtt 14.5 kB
  • ~Get Your Files Here !/43. The Gini index approach-en-US.vtt 14.4 kB
  • ~Get Your Files Here !/07. Linear regression theory optimization-pt.vtt 14.3 kB
  • ~Get Your Files Here !/22. K nearest neighbor implementation II-es-MX.vtt 14.2 kB
  • ~Get Your Files Here !/27. What is text clustering-fr.vtt 14.1 kB
  • ~Get Your Files Here !/27. What is text clustering-de.vtt 14.0 kB
  • ~Get Your Files Here !/41. Decision trees introduction entropy-fr.vtt 14.0 kB
  • ~Get Your Files Here !/63. Principal component analysis example II-en-US.vtt 14.0 kB
  • ~Get Your Files Here !/41. Decision trees introduction entropy-de.vtt 14.0 kB
  • ~Get Your Files Here !/22. K nearest neighbor implementation II-pt.vtt 13.8 kB
  • ~Get Your Files Here !/04. Types of artificial intelligence learning-en-US.vtt 13.7 kB
  • ~Get Your Files Here !/27. What is text clustering-es-MX.vtt 13.6 kB
  • ~Get Your Files Here !/41. Decision trees introduction entropy-es-MX.vtt 13.6 kB
  • ~Get Your Files Here !/08. Linear regression theory gradient descent-fr.vtt 13.6 kB
  • ~Get Your Files Here !/27. What is text clustering-pt.vtt 13.5 kB
  • ~Get Your Files Here !/07. Linear regression theory optimization-en-US.vtt 13.5 kB
  • ~Get Your Files Here !/41. Decision trees introduction entropy-pt.vtt 13.4 kB
  • ~Get Your Files Here !/08. Linear regression theory gradient descent-de.vtt 13.3 kB
  • ~Get Your Files Here !/68. DBSCAN example-en-US.vtt 13.3 kB
  • ~Get Your Files Here !/61. Principal component analysis (PCA) introduction-en-US.vtt 13.2 kB
  • ~Get Your Files Here !/40. Decision trees introduction basics-fr.vtt 13.2 kB
  • ~Get Your Files Here !/08. Linear regression theory gradient descent-es-MX.vtt 13.2 kB
  • ~Get Your Files Here !/22. K nearest neighbor implementation II-en-US.vtt 13.1 kB
  • ~Get Your Files Here !/05. Fundamentals of statistics-de.vtt 12.9 kB
  • ~Get Your Files Here !/27. What is text clustering-en-US.vtt 12.9 kB
  • ~Get Your Files Here !/40. Decision trees introduction basics-de.vtt 12.9 kB
  • ~Get Your Files Here !/41. Decision trees introduction entropy-en-US.vtt 12.8 kB
  • ~Get Your Files Here !/05. Fundamentals of statistics-fr.vtt 12.8 kB
  • ~Get Your Files Here !/42. Decision trees introduction information gain-fr.vtt 12.7 kB
  • ~Get Your Files Here !/08. Linear regression theory gradient descent-pt.vtt 12.7 kB
  • ~Get Your Files Here !/42. Decision trees introduction information gain-de.vtt 12.6 kB
  • ~Get Your Files Here !/40. Decision trees introduction basics-es-MX.vtt 12.6 kB
  • ~Get Your Files Here !/36. Support vector machines example III parameter tuning-fr.vtt 12.5 kB
  • ~Get Your Files Here !/57. Boosting introduction final formula-en-US.vtt 12.5 kB
  • ~Get Your Files Here !/32. Non linearly separable problems-fr.vtt 12.4 kB
  • ~Get Your Files Here !/05. Fundamentals of statistics-es-MX.vtt 12.4 kB
  • ~Get Your Files Here !/42. Decision trees introduction information gain-es-MX.vtt 12.4 kB
  • ~Get Your Files Here !/36. Support vector machines example III parameter tuning-de.vtt 12.3 kB
  • ~Get Your Files Here !/05. Fundamentals of statistics-pt.vtt 12.3 kB
  • ~Get Your Files Here !/08. Linear regression theory gradient descent-en-US.vtt 12.3 kB
  • ~Get Your Files Here !/32. Non linearly separable problems-de.vtt 12.3 kB
  • ~Get Your Files Here !/40. Decision trees introduction basics-pt.vtt 12.3 kB
  • ~Get Your Files Here !/65. K means clustering example-en-US.vtt 12.2 kB
  • ~Get Your Files Here !/19. Distance metrics Euclidean distance-de.vtt 12.2 kB
  • ~Get Your Files Here !/19. Distance metrics Euclidean distance-fr.vtt 12.2 kB
  • ~Get Your Files Here !/70. Hierarchical clustering example-en-US.vtt 12.1 kB
  • ~Get Your Files Here !/49. Bagging introduction-en-US.vtt 12.1 kB
  • ~Get Your Files Here !/42. Decision trees introduction information gain-pt.vtt 12.1 kB
  • ~Get Your Files Here !/36. Support vector machines example III parameter tuning-es-MX.vtt 12.0 kB
  • ~Get Your Files Here !/32. Non linearly separable problems-es-MX.vtt 12.0 kB
  • ~Get Your Files Here !/32. Non linearly separable problems-pt.vtt 11.8 kB
  • ~Get Your Files Here !/05. Fundamentals of statistics-en-US.vtt 11.8 kB
  • ~Get Your Files Here !/36. Support vector machines example III parameter tuning-pt.vtt 11.8 kB
  • ~Get Your Files Here !/19. Distance metrics Euclidean distance-es-MX.vtt 11.8 kB
  • ~Get Your Files Here !/42. Decision trees introduction information gain-en-US.vtt 11.6 kB
  • ~Get Your Files Here !/40. Decision trees introduction basics-en-US.vtt 11.6 kB
  • ~Get Your Files Here !/19. Distance metrics Euclidean distance-pt.vtt 11.6 kB
  • ~Get Your Files Here !/21. K nearest neighbor implementation I-fr.vtt 11.4 kB
  • ~Get Your Files Here !/21. K nearest neighbor implementation I-de.vtt 11.4 kB
  • ~Get Your Files Here !/21. K nearest neighbor implementation I-es-MX.vtt 11.1 kB
  • ~Get Your Files Here !/19. Distance metrics Euclidean distance-en-US.vtt 11.1 kB
  • ~Get Your Files Here !/67. DBSCAN introduction-en-US.vtt 11.1 kB
  • ~Get Your Files Here !/35. Support vector machine example II iris dataset-fr.vtt 11.1 kB
  • ~Get Your Files Here !/32. Non linearly separable problems-en-US.vtt 11.1 kB
  • ~Get Your Files Here !/36. Support vector machines example III parameter tuning-en-US.vtt 11.0 kB
  • ~Get Your Files Here !/21. K nearest neighbor implementation I-pt.vtt 10.9 kB
  • ~Get Your Files Here !/15. What is cross validation-fr.vtt 10.8 kB
  • ~Get Your Files Here !/69. Hierarchical clustering introduction-en-US.vtt 10.8 kB
  • ~Get Your Files Here !/35. Support vector machine example II iris dataset-es-MX.vtt 10.7 kB
  • ~Get Your Files Here !/35. Support vector machine example II iris dataset-de.vtt 10.7 kB
  • ~Get Your Files Here !/56. Boosting introduction equations-en-US.vtt 10.7 kB
  • ~Get Your Files Here !/15. What is cross validation-de.vtt 10.7 kB
  • ~Get Your Files Here !/21. K nearest neighbor implementation I-en-US.vtt 10.6 kB
  • ~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning-fr.vtt 10.5 kB
  • ~Get Your Files Here !/35. Support vector machine example II iris dataset-pt.vtt 10.5 kB
  • ~Get Your Files Here !/17. What is the k nearest neighbor classifier-fr.vtt 10.4 kB
  • ~Get Your Files Here !/17. What is the k nearest neighbor classifier-de.vtt 10.4 kB
  • ~Get Your Files Here !/48. Pruning introduction-en-US.vtt 10.4 kB
  • ~Get Your Files Here !/15. What is cross validation-es-MX.vtt 10.4 kB
  • ~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning-de.vtt 10.3 kB
  • ~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning-es-MX.vtt 10.3 kB
  • ~Get Your Files Here !/45. Decision trees implementation I-fr.vtt 10.3 kB
  • ~Get Your Files Here !/15. What is cross validation-pt.vtt 10.2 kB
  • ~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning-pt.vtt 10.1 kB
  • ~Get Your Files Here !/17. What is the k nearest neighbor classifier-es-MX.vtt 10.1 kB
  • ~Get Your Files Here !/30. What are Support Vector Machines (SVMs)-de.vtt 10.1 kB
  • ~Get Your Files Here !/30. What are Support Vector Machines (SVMs)-fr.vtt 9.9 kB
  • ~Get Your Files Here !/17. What is the k nearest neighbor classifier-pt.vtt 9.9 kB
  • ~Get Your Files Here !/45. Decision trees implementation I-es-MX.vtt 9.8 kB
  • ~Get Your Files Here !/45. Decision trees implementation I-de.vtt 9.7 kB
  • ~Get Your Files Here !/35. Support vector machine example II iris dataset-en-US.vtt 9.7 kB
  • ~Get Your Files Here !/58. Boosting implementation I iris dataset-en-US.vtt 9.7 kB
  • ~Get Your Files Here !/30. What are Support Vector Machines (SVMs)-es-MX.vtt 9.7 kB
  • ~Get Your Files Here !/38. Support vector machine example V digit recognition-fr.vtt 9.7 kB
  • ~Get Your Files Here !/45. Decision trees implementation I-pt.vtt 9.7 kB
  • ~Get Your Files Here !/15. What is cross validation-en-US.vtt 9.5 kB
  • ~Get Your Files Here !/30. What are Support Vector Machines (SVMs)-pt.vtt 9.5 kB
  • ~Get Your Files Here !/03. Why to learn artificial intelligence and machine learning-en-US.vtt 9.4 kB
  • ~Get Your Files Here !/17. What is the k nearest neighbor classifier-en-US.vtt 9.4 kB
  • ~Get Your Files Here !/38. Support vector machine example V digit recognition-de.vtt 9.4 kB
  • ~Get Your Files Here !/38. Support vector machine example V digit recognition-es-MX.vtt 9.3 kB
  • ~Get Your Files Here !/38. Support vector machine example V digit recognition-pt.vtt 9.0 kB
  • ~Get Your Files Here !/30. What are Support Vector Machines (SVMs)-en-US.vtt 8.9 kB
  • ~Get Your Files Here !/45. Decision trees implementation I-en-US.vtt 8.9 kB
  • ~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation-fr.vtt 8.9 kB
  • ~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation-de.vtt 8.8 kB
  • ~Get Your Files Here !/16. Cross validation example-fr.vtt 8.8 kB
  • ~Get Your Files Here !/50. Random forest classifier introduction-en-US.vtt 8.8 kB
  • ~Get Your Files Here !/16. Cross validation example-de.vtt 8.8 kB
  • ~Get Your Files Here !/16. Cross validation example-es-MX.vtt 8.6 kB
  • ~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation-es-MX.vtt 8.5 kB
  • ~Get Your Files Here !/55. Boosting introduction illustration-en-US.vtt 8.5 kB
  • ~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF)-fr.vtt 8.5 kB
  • ~Get Your Files Here !/38. Support vector machine example V digit recognition-en-US.vtt 8.4 kB
  • ~Get Your Files Here !/16. Cross validation example-pt.vtt 8.4 kB
  • ~Get Your Files Here !/47. Decision tree implementation III identifying cancer-fr.vtt 8.2 kB
  • ~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation-pt.vtt 8.2 kB
  • ~Get Your Files Here !/47. Decision tree implementation III identifying cancer-de.vtt 8.2 kB
  • ~Get Your Files Here !/46. Decision trees implementation II parameter tuning-fr.vtt 8.2 kB
  • ~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF)-de.vtt 8.1 kB
  • ~Get Your Files Here !/46. Decision trees implementation II parameter tuning-de.vtt 8.0 kB
  • ~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF)-es-MX.vtt 8.0 kB
  • ~Get Your Files Here !/16. Cross validation example-en-US.vtt 8.0 kB
  • ~Get Your Files Here !/25. Naive Bayes classifier illustration-de.vtt 8.0 kB
  • ~Get Your Files Here !/12. Logistic regression and maximum likelihood estimation-en-US.vtt 7.9 kB
  • ~Get Your Files Here !/47. Decision tree implementation III identifying cancer-es-MX.vtt 7.9 kB
  • ~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF)-pt.vtt 7.9 kB
  • ~Get Your Files Here !/25. Naive Bayes classifier illustration-fr.vtt 7.8 kB
  • ~Get Your Files Here !/46. Decision trees implementation II parameter tuning-es-MX.vtt 7.7 kB
  • ~Get Your Files Here !/25. Naive Bayes classifier illustration-es-MX.vtt 7.7 kB
  • ~Get Your Files Here !/46. Decision trees implementation II parameter tuning-pt.vtt 7.6 kB
  • ~Get Your Files Here !/28. Text clustering inverse document frequency (TF IDF)-en-US.vtt 7.6 kB
  • ~Get Your Files Here !/47. Decision tree implementation III identifying cancer-pt.vtt 7.6 kB
  • ~Get Your Files Here !/25. Naive Bayes classifier illustration-pt.vtt 7.5 kB
  • ~Get Your Files Here !/10. Linear regression implementation II-fr.vtt 7.4 kB
  • ~Get Your Files Here !/47. Decision tree implementation III identifying cancer-en-US.vtt 7.3 kB
  • ~Get Your Files Here !/25. Naive Bayes classifier illustration-en-US.vtt 7.2 kB
  • ~Get Your Files Here !/10. Linear regression implementation II-de.vtt 7.2 kB
  • ~Get Your Files Here !/23. K nearest neighbor implementation III-de.vtt 7.2 kB
  • ~Get Your Files Here !/26. Naive Bayes classifier implementation-fr.vtt 7.2 kB
  • ~Get Your Files Here !/23. K nearest neighbor implementation III-fr.vtt 7.1 kB
  • ~Get Your Files Here !/10. Linear regression implementation II-es-MX.vtt 7.0 kB
  • ~Get Your Files Here !/46. Decision trees implementation II parameter tuning-en-US.vtt 7.0 kB
  • ~Get Your Files Here !/26. Naive Bayes classifier implementation-de.vtt 6.9 kB
  • ~Get Your Files Here !/20. Bias and variance trade off-de.vtt 6.9 kB
  • ~Get Your Files Here !/26. Naive Bayes classifier implementation-es-MX.vtt 6.9 kB
  • ~Get Your Files Here !/23. K nearest neighbor implementation III-es-MX.vtt 6.9 kB
  • ~Get Your Files Here !/10. Linear regression implementation II-pt.vtt 6.8 kB
  • ~Get Your Files Here !/20. Bias and variance trade off-fr.vtt 6.8 kB
  • ~Get Your Files Here !/26. Naive Bayes classifier implementation-pt.vtt 6.8 kB
  • ~Get Your Files Here !/23. K nearest neighbor implementation III-pt.vtt 6.8 kB
  • ~Get Your Files Here !/01. Introduction-fr.vtt 6.7 kB
  • ~Get Your Files Here !/51. Random forests example I iris dataset-en-US.vtt 6.7 kB
  • ~Get Your Files Here !/18. Concept of lazy learning-fr.vtt 6.6 kB
  • ~Get Your Files Here !/10. Linear regression implementation II-en-US.vtt 6.6 kB
  • ~Get Your Files Here !/54. Boosting introduction basics-en-US.vtt 6.6 kB
  • ~Get Your Files Here !/20. Bias and variance trade off-es-MX.vtt 6.5 kB
  • ~Get Your Files Here !/18. Concept of lazy learning-es-MX.vtt 6.5 kB
  • ~Get Your Files Here !/01. Introduction-de.vtt 6.5 kB
  • ~Get Your Files Here !/18. Concept of lazy learning-de.vtt 6.5 kB
  • ~Get Your Files Here !/23. K nearest neighbor implementation III-en-US.vtt 6.4 kB
  • ~Get Your Files Here !/18. Concept of lazy learning-pt.vtt 6.4 kB
  • ~Get Your Files Here !/01. Introduction-es-MX.vtt 6.4 kB
  • ~Get Your Files Here !/20. Bias and variance trade off-pt.vtt 6.4 kB
  • ~Get Your Files Here !/01. Introduction-pt.vtt 6.4 kB
  • ~Get Your Files Here !/26. Naive Bayes classifier implementation-en-US.vtt 6.3 kB
  • ~Get Your Files Here !/20. Bias and variance trade off-en-US.vtt 6.1 kB
  • ~Get Your Files Here !/01. Introduction-en-US.vtt 5.9 kB
  • ~Get Your Files Here !/18. Concept of lazy learning-en-US.vtt 5.9 kB
  • ~Get Your Files Here !/52. Random forests example II credit scoring-en-US.vtt 5.4 kB
  • ~Get Your Files Here !/39. Advantages and disadvantages-de.vtt 5.1 kB
  • ~Get Your Files Here !/39. Advantages and disadvantages-fr.vtt 5.0 kB
  • ~Get Your Files Here !/60. Boosting vs bagging-en-US.vtt 4.9 kB
  • ~Get Your Files Here !/39. Advantages and disadvantages-es-MX.vtt 4.9 kB
  • ~Get Your Files Here !/39. Advantages and disadvantages-pt.vtt 4.8 kB
  • ~Get Your Files Here !/39. Advantages and disadvantages-en-US.vtt 4.5 kB
  • ~Get Your Files Here !/44. Decision trees introduction pros and cons-fr.vtt 4.4 kB
  • ~Get Your Files Here !/44. Decision trees introduction pros and cons-de.vtt 4.4 kB
  • ~Get Your Files Here !/44. Decision trees introduction pros and cons-es-MX.vtt 4.3 kB
  • ~Get Your Files Here !/44. Decision trees introduction pros and cons-pt.vtt 4.2 kB
  • ~Get Your Files Here !/44. Decision trees introduction pros and cons-en-US.vtt 3.9 kB
  • ~Get Your Files Here !/02. Installing TensorFlow and Keras-fr.vtt 3.6 kB
  • ~Get Your Files Here !/02. Installing TensorFlow and Keras-de.vtt 3.6 kB
  • ~Get Your Files Here !/02. Installing TensorFlow and Keras-pt.vtt 3.5 kB
  • ~Get Your Files Here !/02. Installing TensorFlow and Keras-es-MX.vtt 3.4 kB
  • ~Get Your Files Here !/02. Installing TensorFlow and Keras-en-US.vtt 3.3 kB
  • ~Get Your Files Here !/Bonus Resources.txt 386 Bytes
  • Get Bonus Downloads Here.url 180 Bytes

随机展示

相关说明

本站不存储任何资源内容，只收集BT种子元数据(例如文件名和文件大小)和磁力链接(BT种子标识符)，并提供查询服务，是一个完全合法的搜索引擎系统。 网站不提供种子下载服务，用户可以通过第三方链接或磁力链接获取到相关的种子资源。本站也不对BT种子真实性及合法性负责，请用户注意甄别！