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[] Udemy - Spark and Python for Big Data with PySpark

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  • 文件大小:2GB
  • 下载次数:46
  • 最近下载:2021-01-04 04:20:18
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文件列表

  1. 4. AWS EC2 PySpark Set-up/2. Creating the EC2 Instance.mp4 63MB
  2. 17. Spark Streaming with Python/5. Spark Streaming Twitter Project - Part Three.mp4 55MB
  3. 12. Logistic Regression/2. Logistic Regression Example Code Along.mp4 53MB
  4. 10. Introduction to Machine Learning with MLlib/2. Machine Learning with Spark and Python with MLlib.mp4 51MB
  5. 4. AWS EC2 PySpark Set-up/4. Installations on EC2.mp4 50MB
  6. 13. Decision Trees and Random Forests/3. Decision Tress and Random Forest Code Along Examples.mp4 49MB
  7. 1. Introduction to Course/4. What is Spark Why Python.mp4 48MB
  8. 3. Local VirtualBox Set-up/2. Local Installation VirtualBox Part 2.mp4 46MB
  9. 6. AWS EMR Cluster Setup/1. AWS EMR Setup.mp4 45MB
  10. 9. Spark DataFrame Project Exercise/2. DataFrame Project Exercise Solutions.mp4 45MB
  11. 12. Logistic Regression/3. Logistic Regression Code Along.mp4 41MB
  12. 11. Linear Regression/2. Linear Regression Documentation Example.mp4 41MB
  13. 11. Linear Regression/4. Linear Regression Example Code Along.mp4 39MB
  14. 11. Linear Regression/6. Linear Regression Consulting Project Solutions.mp4 39MB
  15. 3. Local VirtualBox Set-up/1. Local Installation VirtualBox Part 1.mp4 38MB
  16. 16. Natural Language Processing/2. NLP Tools Part One.mp4 36MB
  17. 16. Natural Language Processing/4. Natural Language Processing Code Along Project.mp4 35MB
  18. 13. Decision Trees and Random Forests/2. Tree Methods Documentation Examples.mp4 34MB
  19. 12. Logistic Regression/5. Logistic Regression Consulting Project Solutions.mp4 34MB
  20. 17. Spark Streaming with Python/1. Introduction to Streaming with Spark!.mp4 33MB
  21. 7. Python Crash Course/3. Python Crash Course Part One.mp4 30MB
  22. 17. Spark Streaming with Python/4. Spark Streaming Twitter Project - Part Two.mp4 29MB
  23. 8. Spark DataFrame Basics/5. Groupby and Aggregate Operations.mp4 29MB
  24. 17. Spark Streaming with Python/2. Spark Streaming Documentation Example.mp4 29MB
  25. 14. K-means Clustering/3. Clustering Example Code Along.mp4 28MB
  26. 5. Databricks Setup/1. Databricks Setup.mp4 28MB
  27. 8. Spark DataFrame Basics/4. Spark DataFrame Basic Operations.mp4 28MB
  28. 7. Python Crash Course/7. Python Crash Course Exercise Solutions.mp4 25MB
  29. 15. Collaborative Filtering for Recommender Systems/2. Recommender System - Code Along Project.mp4 25MB
  30. 8. Spark DataFrame Basics/7. Dates and Timestamps.mp4 24MB
  31. 7. Python Crash Course/5. Python Crash Course Part Three.mp4 23MB
  32. 14. K-means Clustering/5. Clustering Consulting Project Solutions.mp4 23MB
  33. 7. Python Crash Course/4. Python Crash Course Part Two.mp4 22MB
  34. 8. Spark DataFrame Basics/2. Spark DataFrame Basics.mp4 21MB
  35. 14. K-means Clustering/2. KMeans Clustering Documentation Example.mp4 21MB
  36. 12. Logistic Regression/1. Logistic Regression Theory and Reading.mp4 21MB
  37. 8. Spark DataFrame Basics/3. Spark DataFrame Basics Part Two.mp4 20MB
  38. 10. Introduction to Machine Learning with MLlib/1. Introduction to Machine Learning and ISLR.mp4 19MB
  39. 16. Natural Language Processing/3. NLP Tools Part Two.mp4 19MB
  40. 8. Spark DataFrame Basics/6. Missing Data.mp4 17MB
  41. 13. Decision Trees and Random Forests/5. Random Forest Classification Consulting Project Solutions.mp4 16MB
  42. 3. Local VirtualBox Set-up/3. Setting up PySpark.mp4 16MB
  43. 13. Decision Trees and Random Forests/1. Tree Methods Theory and Reading.mp4 15MB
  44. 1. Introduction to Course/2. Course Overview.mp4 14MB
  45. 16. Natural Language Processing/1. Introduction to Natural Language Processing.mp4 14MB
  46. 7. Python Crash Course/2. Jupyter Notebook Overview.mp4 13MB
  47. 14. K-means Clustering/1. K-means Clustering Theory and Reading.mp4 13MB
  48. 15. Collaborative Filtering for Recommender Systems/1. Introduction to Recommender Systems.mp4 13MB
  49. 11. Linear Regression/3. Regression Evaluation.mp4 12MB
  50. 9. Spark DataFrame Project Exercise/1. DataFrame Project Exercise.mp4 12MB
  51. 17. Spark Streaming with Python/3. Spark Streaming Twitter Project - Part.mp4 12MB
  52. 1. Introduction to Course/1. Introduction.mp4 12MB
  53. 2. Setting up Python with Spark/1. Set-up Overview.mp4 11MB
  54. 11. Linear Regression/1. Linear Regression Theory and Reading.mp4 10MB
  55. 4. AWS EC2 PySpark Set-up/3. SSH with Mac or Linux.mp4 9MB
  56. 11. Linear Regression/5. Linear Regression Consulting Project.mp4 7MB
  57. 14. K-means Clustering/4. Clustering Consulting Project.mp4 7MB
  58. 12. Logistic Regression/4. Logistic Regression Consulting Project.mp4 6MB
  59. 13. Decision Trees and Random Forests/4. Random Forest - Classification Consulting Project.mp4 5MB
  60. 4. AWS EC2 PySpark Set-up/1. AWS EC2 Set-up Guide.mp4 5MB
  61. 7. Python Crash Course/6. Python Crash Course Exercises.mp4 5MB
  62. 8. Spark DataFrame Basics/1. Introduction to Spark DataFrames.mp4 5MB
  63. 7. Python Crash Course/1. Introduction to Python Crash Course.mp4 3MB
  64. 1. Introduction to Course/2.2 Python-and-Spark-for-Big-Data-master.zip.zip 2MB
  65. 1. Introduction to Course/3.1 Python-and-Spark-for-Big-Data-master.zip.zip 2MB
  66. 11. Linear Regression/4.1 Ecommerce_Customers.csv.csv 85KB
  67. 13. Decision Trees and Random Forests/3. Decision Tress and Random Forest Code Along Examples.srt 31KB
  68. 1. Introduction to Course/4. What is Spark Why Python.srt 31KB
  69. 17. Spark Streaming with Python/5. Spark Streaming Twitter Project - Part Three.srt 29KB
  70. 12. Logistic Regression/3. Logistic Regression Code Along.srt 27KB
  71. 6. AWS EMR Cluster Setup/1. AWS EMR Setup.srt 26KB
  72. 4. AWS EC2 PySpark Set-up/2. Creating the EC2 Instance.srt 24KB
  73. 7. Python Crash Course/3. Python Crash Course Part One.srt 24KB
  74. 12. Logistic Regression/2. Logistic Regression Example Code Along.srt 24KB
  75. 11. Linear Regression/4. Linear Regression Example Code Along.srt 23KB
  76. 16. Natural Language Processing/2. NLP Tools Part One.srt 23KB
  77. 11. Linear Regression/6. Linear Regression Consulting Project Solutions.srt 23KB
  78. 9. Spark DataFrame Project Exercise/2. DataFrame Project Exercise Solutions.srt 22KB
  79. 11. Linear Regression/2. Linear Regression Documentation Example.srt 22KB
  80. 13. Decision Trees and Random Forests/2. Tree Methods Documentation Examples.srt 21KB
  81. 4. AWS EC2 PySpark Set-up/4. Installations on EC2.srt 20KB
  82. 16. Natural Language Processing/4. Natural Language Processing Code Along Project.srt 20KB
  83. 8. Spark DataFrame Basics/5. Groupby and Aggregate Operations.srt 19KB
  84. 5. Databricks Setup/1. Databricks Setup.srt 19KB
  85. 3. Local VirtualBox Set-up/2. Local Installation VirtualBox Part 2.srt 19KB
  86. 14. K-means Clustering/3. Clustering Example Code Along.srt 19KB
  87. 3. Local VirtualBox Set-up/1. Local Installation VirtualBox Part 1.srt 18KB
  88. 17. Spark Streaming with Python/4. Spark Streaming Twitter Project - Part Two.srt 18KB
  89. 15. Collaborative Filtering for Recommender Systems/2. Recommender System - Code Along Project.srt 18KB
  90. 12. Logistic Regression/1. Logistic Regression Theory and Reading.srt 18KB
  91. 10. Introduction to Machine Learning with MLlib/1. Introduction to Machine Learning and ISLR.srt 18KB
  92. 7. Python Crash Course/4. Python Crash Course Part Two.srt 18KB
  93. 17. Spark Streaming with Python/1. Introduction to Streaming with Spark!.srt 17KB
  94. 17. Spark Streaming with Python/2. Spark Streaming Documentation Example.srt 17KB
  95. 8. Spark DataFrame Basics/2. Spark DataFrame Basics.srt 16KB
  96. 7. Python Crash Course/5. Python Crash Course Part Three.srt 16KB
  97. 8. Spark DataFrame Basics/4. Spark DataFrame Basic Operations.srt 16KB
  98. 10. Introduction to Machine Learning with MLlib/2. Machine Learning with Spark and Python with MLlib.srt 16KB
  99. 12. Logistic Regression/5. Logistic Regression Consulting Project Solutions.srt 15KB
  100. 1. Introduction to Course/2. Course Overview.srt 15KB
  101. 14. K-means Clustering/2. KMeans Clustering Documentation Example.srt 15KB
  102. 8. Spark DataFrame Basics/7. Dates and Timestamps.srt 15KB
  103. 8. Spark DataFrame Basics/3. Spark DataFrame Basics Part Two.srt 14KB
  104. 8. Spark DataFrame Basics/6. Missing Data.srt 13KB
  105. 16. Natural Language Processing/1. Introduction to Natural Language Processing.srt 13KB
  106. 7. Python Crash Course/7. Python Crash Course Exercise Solutions.srt 13KB
  107. 13. Decision Trees and Random Forests/5. Random Forest Classification Consulting Project Solutions.srt 12KB
  108. 13. Decision Trees and Random Forests/1. Tree Methods Theory and Reading.srt 12KB
  109. 14. K-means Clustering/5. Clustering Consulting Project Solutions.srt 12KB
  110. 7. Python Crash Course/2. Jupyter Notebook Overview.srt 11KB
  111. 11. Linear Regression/3. Regression Evaluation.srt 11KB
  112. 16. Natural Language Processing/3. NLP Tools Part Two.srt 11KB
  113. 14. K-means Clustering/1. K-means Clustering Theory and Reading.srt 11KB
  114. 2. Setting up Python with Spark/1. Set-up Overview.srt 10KB
  115. 15. Collaborative Filtering for Recommender Systems/1. Introduction to Recommender Systems.srt 10KB
  116. 3. Local VirtualBox Set-up/3. Setting up PySpark.srt 8KB
  117. 11. Linear Regression/1. Linear Regression Theory and Reading.srt 8KB
  118. 4. AWS EC2 PySpark Set-up/3. SSH with Mac or Linux.srt 7KB
  119. 17. Spark Streaming with Python/3. Spark Streaming Twitter Project - Part.srt 7KB
  120. 9. Spark DataFrame Project Exercise/1. DataFrame Project Exercise.srt 5KB
  121. 12. Logistic Regression/4. Logistic Regression Consulting Project.srt 5KB
  122. 11. Linear Regression/5. Linear Regression Consulting Project.srt 5KB
  123. 14. K-means Clustering/4. Clustering Consulting Project.srt 5KB
  124. 1. Introduction to Course/1. Introduction.srt 4KB
  125. 4. AWS EC2 PySpark Set-up/1. AWS EC2 Set-up Guide.srt 4KB
  126. 13. Decision Trees and Random Forests/4. Random Forest - Classification Consulting Project.srt 4KB
  127. 8. Spark DataFrame Basics/1. Introduction to Spark DataFrames.srt 4KB
  128. 7. Python Crash Course/6. Python Crash Course Exercises.srt 2KB
  129. 7. Python Crash Course/1. Introduction to Python Crash Course.srt 2KB
  130. 18. Bonus/1. Bonus Lecture.html 532B
  131. 1. Introduction to Course/3. Frequently Asked Questions.html 447B
  132. 2. Setting up Python with Spark/2. Note on Installation Sections.html 347B
  133. 1. Introduction to Course/2.1 Course Overview Slides.html 161B
  134. 1. Introduction to Course/4.1 Spark and Python Slides.html 161B
  135. 10. Introduction to Machine Learning with MLlib/1.1 Slides for ML Intro.html 161B
  136. 11. Linear Regression/1.1 Slides for Linear Regression.html 161B
  137. 12. Logistic Regression/1.1 Slides for Logistic Regression.html 161B
  138. 13. Decision Trees and Random Forests/1.1 Slides for Tree Methods.html 161B
  139. 14. K-means Clustering/1.1 Slides for Clustering.html 161B
  140. 15. Collaborative Filtering for Recommender Systems/1.1 Recommender Slides.html 161B
  141. 16. Natural Language Processing/1.1 NLP Slides.html 161B
  142. 17. Spark Streaming with Python/1.1 Spark Streaming Slides.html 161B
  143. 2. Setting up Python with Spark/1.1 Slides for Installation Options Overview.html 161B
  144. 2. Setting up Python with Spark/1.2 Slides for Installation.html 161B
  145. 7. Python Crash Course/1.1 Slides for Python Crash Course.html 161B
  146. 8. Spark DataFrame Basics/1.1 Slides for Spark DataFrame Basics.html 161B
  147. 12. Logistic Regression/3.2 Great Example from Databricks.html 150B
  148. 12. Logistic Regression/3.1 Explanation of AUC.html 148B
  149. [FreeCourseWorld.Com].url 54B
  150. [DesireCourse.Net].url 51B
  151. [CourseClub.Me].url 48B