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[] Udemy - Machine Learning, Data Science and Deep Learning with Python

  • 收录时间:2019-06-26 16:25:47
  • 文件大小:7GB
  • 下载次数:71
  • 最近下载:2021-01-15 11:51:35
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文件列表

  1. 8. Apache Spark Machine Learning on Big Data/8. [Activity] Decision Trees in Spark.mp4 193MB
  2. 8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.mp4 172MB
  3. 6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.mp4 142MB
  4. 10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.mp4 142MB
  5. 1. Getting Started/5. Python Basics, Part 1 [Optional].mp4 134MB
  6. 8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.mp4 134MB
  7. 10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 2.mp4 134MB
  8. 5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.mp4 133MB
  9. 6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.mp4 132MB
  10. 2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.mp4 130MB
  11. 7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.mp4 129MB
  12. 2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.mp4 129MB
  13. 10. Deep Learning and Neural Networks/14. The Ethics of Deep Learning.mp4 128MB
  14. 1. Getting Started/8. Introducing the Pandas Library [Optional].mp4 128MB
  15. 3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.mp4 124MB
  16. 2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.mp4 117MB
  17. 2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.mp4 114MB
  18. 8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.mp4 114MB
  19. 8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.mp4 112MB
  20. 2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.mp4 111MB
  21. 6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.mp4 110MB
  22. 1. Getting Started/4. [Activity] Installing Enthought Canopy.mp4 109MB
  23. 5. Recommender Systems/3. [Activity] Finding Movie Similarities.mp4 108MB
  24. 10. Deep Learning and Neural Networks/8. [Activity] Introducing Keras.mp4 107MB
  25. 10. Deep Learning and Neural Networks/9. [Activity] Using Keras to Predict Political Affiliations.mp4 104MB
  26. 6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.mp4 103MB
  27. 7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.mp4 102MB
  28. 10. Deep Learning and Neural Networks/6. [Activity] Using Tensorflow, Part 1.mp4 102MB
  29. 3. Predictive Models/1. [Activity] Linear Regression.mp4 100MB
  30. 4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.mp4 99MB
  31. 8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).mp4 99MB
  32. 11. Final Project/2. Final project review.mp4 99MB
  33. 9. Experimental Design/1. AB Testing Concepts.mp4 97MB
  34. 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.mp4 96MB
  35. 9. Experimental Design/5. AB Test Gotchas.mp4 96MB
  36. 4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.mp4 96MB
  37. 5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.mp4 95MB
  38. 10. Deep Learning and Neural Networks/13. [Activity] Using a RNN for sentiment analysis.mp4 95MB
  39. 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).mp4 93MB
  40. 2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.mp4 93MB
  41. 8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.mp4 90MB
  42. 4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.mp4 89MB
  43. 8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.mp4 87MB
  44. 4. Machine Learning with Python/9. Decision Trees Concepts.mp4 87MB
  45. 5. Recommender Systems/1. User-Based Collaborative Filtering.mp4 86MB
  46. 5. Recommender Systems/6. [Exercise] Improve the recommender's results.mp4 84MB
  47. 7. Dealing with Real-World Data/6. [Activity] Detecting outliers.mp4 84MB
  48. 9. Experimental Design/3. [Activity] Hands-on With T-Tests.mp4 82MB
  49. 10. Deep Learning and Neural Networks/11. [Activity] Using CNN's for handwriting recognition.mp4 81MB
  50. 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.mp4 80MB
  51. 7. Dealing with Real-World Data/3. Data Cleaning and Normalization.mp4 79MB
  52. 2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.mp4 77MB
  53. 1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].mp4 77MB
  54. 2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.mp4 75MB
  55. 5. Recommender Systems/2. Item-Based Collaborative Filtering.mp4 75MB
  56. 4. Machine Learning with Python/5. K-Means Clustering.mp4 72MB
  57. 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).mp4 69MB
  58. 8. Apache Spark Machine Learning on Big Data/10. TF IDF.mp4 69MB
  59. 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.mp4 68MB
  60. 6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.mp4 68MB
  61. 3. Predictive Models/2. [Activity] Polynomial Regression.mp4 67MB
  62. 7. Dealing with Real-World Data/1. BiasVariance Tradeoff.mp4 66MB
  63. 4. Machine Learning with Python/11. Ensemble Learning.mp4 65MB
  64. 9. Experimental Design/2. T-Tests and P-Values.mp4 65MB
  65. 10. Deep Learning and Neural Networks/4. Deep Learning Details.mp4 64MB
  66. 12. You made it!/1. More to Explore.mp4 64MB
  67. 1. Getting Started/1. Introduction.mp4 60MB
  68. 2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.mp4 59MB
  69. 11. Final Project/1. Your final project assignment.mp4 59MB
  70. 4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.mp4 58MB
  71. 4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.mp4 57MB
  72. 2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.mp4 56MB
  73. 4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.mp4 55MB
  74. 8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.mp4 55MB
  75. 3. Predictive Models/4. Multi-Level Models.mp4 47MB
  76. 4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.mp4 45MB
  77. 1. Getting Started/7. Running Python Scripts [Optional].mp4 45MB
  78. 4. Machine Learning with Python/3. Bayesian Methods Concepts.mp4 41MB
  79. 6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.mp4 40MB
  80. 10. Deep Learning and Neural Networks/15. Learning More about Deep Learning.mp4 39MB
  81. 7. Dealing with Real-World Data/5. Normalizing numerical data.mp4 38MB
  82. 4. Machine Learning with Python/7. Measuring Entropy.mp4 35MB
  83. 9. Experimental Design/4. Determining How Long to Run an Experiment.mp4 35MB
  84. 2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.mp4 30MB
  85. 2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.mp4 29MB
  86. 1. Getting Started/3. [Activity] Getting What You Need.mp4 28MB
  87. 1. Getting Started/2. Udemy 101 Getting the Most From This Course.mp4 20MB
  88. 1. Getting Started/5. Python Basics, Part 1 [Optional].vtt 32KB
  89. 8. Apache Spark Machine Learning on Big Data/8. [Activity] Decision Trees in Spark.vtt 29KB
  90. 10. Deep Learning and Neural Networks/8. [Activity] Introducing Keras.vtt 29KB
  91. 10. Deep Learning and Neural Networks/9. [Activity] Using Keras to Predict Political Affiliations.vtt 26KB
  92. 2. Statistics and Probability Refresher, and Python Practise/8. [Activity] A Crash Course in matplotlib.vtt 26KB
  93. 6. More Data Mining and Machine Learning Techniques/6. Reinforcement Learning.vtt 26KB
  94. 6. More Data Mining and Machine Learning Techniques/2. [Activity] Using KNN to predict a rating for a movie.vtt 26KB
  95. 8. Apache Spark Machine Learning on Big Data/4. [Activity] Installing Spark - Part 2.vtt 26KB
  96. 2. Statistics and Probability Refresher, and Python Practise/7. [Activity] Percentiles and Moments.vtt 25KB
  97. 2. Statistics and Probability Refresher, and Python Practise/9. [Activity] Covariance and Correlation.vtt 23KB
  98. 2. Statistics and Probability Refresher, and Python Practise/4. [Activity] Variation and Standard Deviation.vtt 23KB
  99. 2. Statistics and Probability Refresher, and Python Practise/10. [Exercise] Conditional Probability.vtt 23KB
  100. 3. Predictive Models/1. [Activity] Linear Regression.vtt 23KB
  101. 3. Predictive Models/3. [Activity] Multivariate Regression, and Predicting Car Prices.vtt 23KB
  102. 8. Apache Spark Machine Learning on Big Data/6. Spark and the Resilient Distributed Dataset (RDD).vtt 22KB
  103. 11. Final Project/2. Final project review.vtt 22KB
  104. 7. Dealing with Real-World Data/2. [Activity] K-Fold Cross-Validation to avoid overfitting.vtt 22KB
  105. 7. Dealing with Real-World Data/4. [Activity] Cleaning web log data.vtt 22KB
  106. 10. Deep Learning and Neural Networks/13. [Activity] Using a RNN for sentiment analysis.vtt 21KB
  107. 5. Recommender Systems/5. [Activity] Making Movie Recommendations to People.vtt 20KB
  108. 4. Machine Learning with Python/10. [Activity] Decision Trees Predicting Hiring Decisions.vtt 20KB
  109. 8. Apache Spark Machine Learning on Big Data/9. [Activity] K-Means Clustering in Spark.vtt 20KB
  110. 9. Experimental Design/5. AB Test Gotchas.vtt 20KB
  111. 10. Deep Learning and Neural Networks/5. Introducing Tensorflow.vtt 20KB
  112. 10. Deep Learning and Neural Networks/7. [Activity] Using Tensorflow, Part 2.vtt 19KB
  113. 10. Deep Learning and Neural Networks/6. [Activity] Using Tensorflow, Part 1.vtt 19KB
  114. 8. Apache Spark Machine Learning on Big Data/5. Spark Introduction.vtt 19KB
  115. 6. More Data Mining and Machine Learning Techniques/4. [Activity] PCA Example with the Iris data set.vtt 19KB
  116. 4. Machine Learning with Python/9. Decision Trees Concepts.vtt 19KB
  117. 4. Machine Learning with Python/1. Supervised vs. Unsupervised Learning, and TrainTest.vtt 19KB
  118. 1. Getting Started/6. [Activity] Python Basics, Part 2 [Optional].vtt 19KB
  119. 9. Experimental Design/1. AB Testing Concepts.vtt 18KB
  120. 5. Recommender Systems/3. [Activity] Finding Movie Similarities.vtt 18KB
  121. 5. Recommender Systems/2. Item-Based Collaborative Filtering.vtt 18KB
  122. 6. More Data Mining and Machine Learning Techniques/5. Data Warehousing Overview ETL and ELT.vtt 18KB
  123. 10. Deep Learning and Neural Networks/10. Convolutional Neural Networks (CNN's).vtt 18KB
  124. 5. Recommender Systems/1. User-Based Collaborative Filtering.vtt 18KB
  125. 10. Deep Learning and Neural Networks/14. The Ethics of Deep Learning.vtt 17KB
  126. 10. Deep Learning and Neural Networks/1. Deep Learning Pre-Requisites.vtt 17KB
  127. 10. Deep Learning and Neural Networks/3. [Activity] Deep Learning in the Tensorflow Playground.vtt 17KB
  128. 10. Deep Learning and Neural Networks/2. The History of Artificial Neural Networks.vtt 17KB
  129. 2. Statistics and Probability Refresher, and Python Practise/3. [Activity] Using mean, median, and mode in Python.vtt 17KB
  130. 10. Deep Learning and Neural Networks/12. Recurrent Neural Networks (RNN's).vtt 16KB
  131. 10. Deep Learning and Neural Networks/11. [Activity] Using CNN's for handwriting recognition.vtt 16KB
  132. 3. Predictive Models/2. [Activity] Polynomial Regression.vtt 16KB
  133. 4. Machine Learning with Python/4. [Activity] Implementing a Spam Classifier with Naive Bayes.vtt 16KB
  134. 8. Apache Spark Machine Learning on Big Data/12. [Activity] Using the Spark 2.0 DataFrame API for MLLib.vtt 16KB
  135. 1. Getting Started/8. Introducing the Pandas Library [Optional].vtt 16KB
  136. 4. Machine Learning with Python/5. K-Means Clustering.vtt 16KB
  137. 7. Dealing with Real-World Data/3. Data Cleaning and Normalization.vtt 15KB
  138. 5. Recommender Systems/4. [Activity] Improving the Results of Movie Similarities.vtt 15KB
  139. 8. Apache Spark Machine Learning on Big Data/3. [Activity] Installing Spark - Part 1.vtt 15KB
  140. 10. Deep Learning and Neural Networks/4. Deep Learning Details.vtt 15KB
  141. 2. Statistics and Probability Refresher, and Python Practise/1. Types of Data.vtt 15KB
  142. 2. Statistics and Probability Refresher, and Python Practise/6. Common Data Distributions.vtt 15KB
  143. 7. Dealing with Real-World Data/6. [Activity] Detecting outliers.vtt 14KB
  144. 8. Apache Spark Machine Learning on Big Data/11. [Activity] Searching Wikipedia with Spark.vtt 14KB
  145. 4. Machine Learning with Python/11. Ensemble Learning.vtt 13KB
  146. 7. Dealing with Real-World Data/1. BiasVariance Tradeoff.vtt 13KB
  147. 8. Apache Spark Machine Learning on Big Data/10. TF IDF.vtt 13KB
  148. 1. Getting Started/4. [Activity] Installing Enthought Canopy.vtt 12KB
  149. 9. Experimental Design/3. [Activity] Hands-on With T-Tests.vtt 12KB
  150. 9. Experimental Design/2. T-Tests and P-Values.vtt 12KB
  151. 5. Recommender Systems/6. [Exercise] Improve the recommender's results.vtt 12KB
  152. 4. Machine Learning with Python/2. [Activity] Using TrainTest to Prevent Overfitting a Polynomial Regression.vtt 12KB
  153. 2. Statistics and Probability Refresher, and Python Practise/2. Mean, Median, Mode.vtt 12KB
  154. 6. More Data Mining and Machine Learning Techniques/3. Dimensionality Reduction; Principal Component Analysis.vtt 11KB
  155. 4. Machine Learning with Python/13. [Activity] Using SVM to cluster people using scikit-learn.vtt 11KB
  156. 4. Machine Learning with Python/6. [Activity] Clustering people based on income and age.vtt 10KB
  157. 2. Statistics and Probability Refresher, and Python Practise/12. Bayes' Theorem.vtt 10KB
  158. 8. Apache Spark Machine Learning on Big Data/7. Introducing MLLib.vtt 10KB
  159. 11. Final Project/1. Your final project assignment.vtt 10KB
  160. 3. Predictive Models/4. Multi-Level Models.vtt 10KB
  161. 4. Machine Learning with Python/12. Support Vector Machines (SVM) Overview.vtt 9KB
  162. 1. Getting Started/7. Running Python Scripts [Optional].vtt 8KB
  163. 6. More Data Mining and Machine Learning Techniques/1. K-Nearest-Neighbors Concepts.vtt 8KB
  164. 4. Machine Learning with Python/3. Bayesian Methods Concepts.vtt 8KB
  165. 9. Experimental Design/4. Determining How Long to Run an Experiment.vtt 8KB
  166. 12. You made it!/3. Bonus Lecture Discounts to continue your journey!.html 7KB
  167. 7. Dealing with Real-World Data/5. Normalizing numerical data.vtt 7KB
  168. 2. Statistics and Probability Refresher, and Python Practise/5. Probability Density Function; Probability Mass Function.vtt 7KB
  169. 12. You made it!/1. More to Explore.vtt 7KB
  170. 4. Machine Learning with Python/7. Measuring Entropy.vtt 6KB
  171. 2. Statistics and Probability Refresher, and Python Practise/11. Exercise Solution Conditional Probability of Purchase by Age.vtt 4KB
  172. 1. Getting Started/1. Introduction.vtt 4KB
  173. 1. Getting Started/3. [Activity] Getting What You Need.vtt 4KB
  174. 1. Getting Started/2. Udemy 101 Getting the Most From This Course.vtt 4KB
  175. 8. Apache Spark Machine Learning on Big Data/2. Spark installation notes for MacOS and Linux users.html 3KB
  176. 10. Deep Learning and Neural Networks/15. Learning More about Deep Learning.vtt 3KB
  177. 4. Machine Learning with Python/8. [Activity] Install GraphViz.html 1KB
  178. 8. Apache Spark Machine Learning on Big Data/1. Warning about Java 11 and Spark 2.4!.html 615B
  179. 12. You made it!/2. Don't Forget to Leave a Rating!.html 564B
  180. 6. More Data Mining and Machine Learning Techniques/6.2 Pac-Man Example.html 145B
  181. 6. More Data Mining and Machine Learning Techniques/6.1 Cat and Mouse Example.html 140B
  182. [FreeCourseLab.com].url 126B
  183. 6. More Data Mining and Machine Learning Techniques/6.3 Python Markov Decision Process Toolbox.html 119B
  184. 1. Getting Started/3.1 Course Facebook Group.html 109B
  185. 8. Apache Spark Machine Learning on Big Data/3.1 winutils.exe.html 108B
  186. 8. Apache Spark Machine Learning on Big Data/4.1 winutils.exe.html 108B
  187. 1. Getting Started/3.2 Course materials and setup steps.html 100B
  188. 1. Getting Started/4.1 Enthought Canopy website.html 86B