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[] Udemy - The Data Science Course Complete Data Science Bootcamp 2023

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文件列表

  1. 11 - Probability Bayesian Inference/51 - A Practical Example of Bayesian Inference.mp4 299MB
  2. 12 - Probability Distributions/66 - A Practical Example of Probability Distributions.mp4 284MB
  3. 16 - Statistics Practical Example Descriptive Statistics/93 - Practical Example Descriptive Statistics.mp4 247MB
  4. 35 - Advanced Statistical Methods Practical Example Linear Regression/224 - Practical Example Linear Regression Part 1.mp4 176MB
  5. 5 - The Field of Data Science Popular Data Science Techniques/11 - Techniques for Working with Traditional Data.mp4 166MB
  6. 64 - Appendix Working with Text Files in Python/505 - Importing Data from json Files.mp4 160MB
  7. 58 - Case Study Preprocessing the Absenteeismdata/420 - Obtaining Dummies from a Single Feature.mp4 152MB
  8. 55 - Appendix Deep Learning TensorFlow 1 Business Case/393 - Business Case Preprocessing.mp4 146MB
  9. 51 - Deep Learning Business Case Example/354 - Business Case Preprocessing the Data.mp4 145MB
  10. 3 - The Field of Data Science Connecting the Data Science Disciplines/9 - Applying Traditional Data Big Data BI Traditional Data Science and ML.mp4 135MB
  11. 19 - Statistics Practical Example Inferential Statistics/118 - Practical Example Inferential Statistics.mp4 134MB
  12. 6 - The Field of Data Science Popular Data Science Tools/22 - Necessary Programming Languages and Software Used in Data Science.mp4 132MB
  13. 55 - Appendix Deep Learning TensorFlow 1 Business Case/390 - Business Case Getting Acquainted with the Dataset.mp4 125MB
  14. 58 - Case Study Preprocessing the Absenteeismdata/425 - Classifying the Various Reasons for Absence.mp4 123MB
  15. 10 - Probability Combinatorics/39 - A Practical Example of Combinatorics.mp4 121MB
  16. 58 - Case Study Preprocessing the Absenteeismdata/412 - Checking the Content of the Data Set.mp4 116MB
  17. 40 - Part 6 Mathematics/281 - Why is Linear Algebra Useful.mp4 113MB
  18. 5 - The Field of Data Science Popular Data Science Techniques/17 - Techniques for Working with Traditional Methods.mp4 113MB
  19. 64 - Appendix Working with Text Files in Python/502 - Importing Data with loadtxt and genfromtxt.mp4 111MB
  20. 55 - Appendix Deep Learning TensorFlow 1 Business Case/395 - Creating a Data Provider.mp4 110MB
  21. 5 - The Field of Data Science Popular Data Science Techniques/20 - Types of Machine Learning.mp4 109MB
  22. 64 - Appendix Working with Text Files in Python/498 - Importing csv Files Part I.mp4 104MB
  23. 35 - Advanced Statistical Methods Practical Example Linear Regression/231 - Practical Example Linear Regression Part 5.mp4 103MB
  24. 51 - Deep Learning Business Case Example/351 - Business Case Exploring the Dataset and Identifying Predictors.mp4 101MB
  25. 18 - Statistics Inferential Statistics Confidence Intervals/104 - Confidence Intervals Population Variance Known Zscore.mp4 101MB
  26. 5 - The Field of Data Science Popular Data Science Techniques/13 - Techniques for Working with Big Data.mp4 101MB
  27. 60 - Case Study Loading the absenteeismmodule/461 - Deploying the absenteeismmodule Part II.mp4 101MB
  28. 56 - Software Integration/404 - Taking a Closer Look at APIs.mp4 97MB
  29. 8 - The Field of Data Science Debunking Common Misconceptions/24 - Debunking Common Misconceptions.mp4 96MB
  30. 18 - Statistics Inferential Statistics Confidence Intervals/111 - Confidence intervals Two means Dependent samples.mp4 92MB
  31. 4 - The Field of Data Science The Benefits of Each Discipline/10 - The Reason Behind These Disciplines.mp4 91MB
  32. 55 - Appendix Deep Learning TensorFlow 1 Business Case/396 - Business Case Model Outline.mp4 89MB
  33. 64 - Appendix Working with Text Files in Python/500 - Importing csv Files Part III.mp4 89MB
  34. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/387 - MNIST Results and Testing.mp4 88MB
  35. 64 - Appendix Working with Text Files in Python/506 - An Introduction to Working with Excel Files in Python.mp4 88MB
  36. 64 - Appendix Working with Text Files in Python/508 - Importing Data in Python an Important Exercise.mp4 88MB
  37. 56 - Software Integration/403 - What are Data Connectivity APIs and Endpoints.mp4 87MB
  38. 64 - Appendix Working with Text Files in Python/503 - Importing Data Partial Cleaning While Importing Data.mp4 86MB
  39. 21 - Statistics Practical Example Hypothesis Testing/135 - Practical Example Hypothesis Testing.mp4 85MB
  40. 51 - Deep Learning Business Case Example/359 - Business Case Setting an Early Stopping Mechanism.mp4 85MB
  41. 58 - Case Study Preprocessing the Absenteeismdata/416 - Dropping a Column from a DataFrame in Python.mp4 81MB
  42. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/450 - Interpreting the Coefficients for Our Problem.mp4 80MB
  43. 61 - Case Study Analyzing the Predicted Outputs in Tableau/466 - Analyzing Reasons vs Probability in Tableau.mp4 80MB
  44. 58 - Case Study Preprocessing the Absenteeismdata/436 - Extracting the Month Value from the Date Column.mp4 77MB
  45. 61 - Case Study Analyzing the Predicted Outputs in Tableau/464 - Analyzing Age vs Probability in Tableau.mp4 77MB
  46. 35 - Advanced Statistical Methods Practical Example Linear Regression/229 - Practical Example Linear Regression Part 4.mp4 76MB
  47. 2 - The Field of Data Science The Various Data Science Disciplines/8 - A Breakdown of our Data Science Infographic.mp4 74MB
  48. 63 - Appendix pandas Fundamentals/485 - Data Selection in pandas DataFrames.mp4 74MB
  49. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/448 - Fitting the Model and Assessing its Accuracy.mp4 73MB
  50. 40 - Part 6 Mathematics/280 - Dot Product of Matrices.mp4 73MB
  51. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/447 - Splitting the Data for Training and Testing.mp4 70MB
  52. 5 - The Field of Data Science Popular Data Science Techniques/15 - Business Intelligence BI Techniques.mp4 70MB
  53. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/202 - Dealing with Categorical Data Dummy Variables.mp4 69MB
  54. 34 - Advanced Statistical Methods Linear Regression with sklearn/223 - Train Test Split Explained.mp4 68MB
  55. 1 - Part 1 Introduction/1 - A Practical Example What You Will Learn in This Course.mp4 68MB
  56. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/193 - Adjusted RSquared.mp4 67MB
  57. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/451 - Standardizing only the Numerical Variables Creating a Custom Scaler.mp4 67MB
  58. 20 - Statistics Hypothesis Testing/129 - Test for the Mean Dependent Samples.mp4 66MB
  59. 9 - Part 2 Probability/26 - Computing Expected Values.mp4 66MB
  60. 5 - The Field of Data Science Popular Data Science Techniques/19 - Machine Learning ML Techniques.mp4 66MB
  61. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/382 - MNIST Model Outline.mp4 66MB
  62. 38 - Advanced Statistical Methods KMeans Clustering/254 - A Simple Example of Clustering.mp4 65MB
  63. 22 - Part 4 Introduction to Python/140 - Installing Python and Jupyter.mp4 65MB
  64. 15 - Statistics Descriptive Statistics/71 - Types of Data.mp4 65MB
  65. 62 - Appendix Additional Python Tools/472 - Triple Nested For Loops.mp4 64MB
  66. 38 - Advanced Statistical Methods KMeans Clustering/264 - Market Segmentation with Cluster Analysis Part 2.mp4 64MB
  67. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/444 - Creating the Targets for the Logistic Regression.mp4 63MB
  68. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/453 - Backward Elimination or How to Simplify Your Model.mp4 63MB
  69. 28 - Python Sequences/169 - Dictionaries.mp4 63MB
  70. 13 - Probability Probability in Other Fields/67 - Probability in Finance.mp4 63MB
  71. 56 - Software Integration/406 - Software Integration Explained.mp4 62MB
  72. 63 - Appendix pandas Fundamentals/486 - pandas DataFrames Indexing with iloc.mp4 62MB
  73. 35 - Advanced Statistical Methods Practical Example Linear Regression/225 - Practical Example Linear Regression Part 2.mp4 62MB
  74. 51 - Deep Learning Business Case Example/358 - Business Case Learning and Interpreting the Result.mp4 61MB
  75. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/454 - Testing the Model We Created.mp4 61MB
  76. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/386 - MNIST Learning.mp4 60MB
  77. 34 - Advanced Statistical Methods Linear Regression with sklearn/207 - Simple Linear Regression with sklearn.mp4 60MB
  78. 20 - Statistics Hypothesis Testing/122 - Rejection Region and Significance Level.mp4 59MB
  79. 50 - Deep Learning Classifying on the MNIST Dataset/348 - MNIST Learning.mp4 59MB
  80. 7 - The Field of Data Science Careers in Data Science/23 - Finding the Job What to Expect and What to Look for.mp4 58MB
  81. 63 - Appendix pandas Fundamentals/480 - Using unique and nunique.mp4 57MB
  82. 32 - Advanced Statistical Methods Linear Regression with StatsModels/185 - First Regression in Python.mp4 56MB
  83. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/199 - A3 Normality and Homoscedasticity.mp4 56MB
  84. 58 - Case Study Preprocessing the Absenteeismdata/426 - Using concat in Python.mp4 55MB
  85. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/458 - Preparing the Deployment of the Model through a Module.mp4 55MB
  86. 2 - The Field of Data Science The Various Data Science Disciplines/7 - Continuing with BI ML and AI.mp4 55MB
  87. 12 - Probability Distributions/59 - Characteristics of Continuous Distributions.mp4 55MB
  88. 38 - Advanced Statistical Methods KMeans Clustering/258 - How to Choose the Number of Clusters.mp4 54MB
  89. 32 - Advanced Statistical Methods Linear Regression with StatsModels/188 - How to Interpret the Regression Table.mp4 54MB
  90. 34 - Advanced Statistical Methods Linear Regression with sklearn/219 - Feature Selection through Standardization of Weights.mp4 54MB
  91. 58 - Case Study Preprocessing the Absenteeismdata/419 - Analyzing the Reasons for Absence.mp4 54MB
  92. 44 - Deep Learning TensorFlow 20 Introduction/300 - How to Install TensorFlow 20.mp4 54MB
  93. 38 - Advanced Statistical Methods KMeans Clustering/263 - Market Segmentation with Cluster Analysis Part 1.mp4 54MB
  94. 17 - Statistics Inferential Statistics Fundamentals/97 - The Normal Distribution.mp4 54MB
  95. 15 - Statistics Descriptive Statistics/73 - Categorical Variables Visualization Techniques.mp4 53MB
  96. 14 - Part 3 Statistics/70 - Population and Sample.mp4 53MB
  97. 9 - Part 2 Probability/27 - Frequency.mp4 53MB
  98. 32 - Advanced Statistical Methods Linear Regression with StatsModels/190 - What is the OLS.mp4 52MB
  99. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/449 - Creating a Summary Table with the Coefficients and Intercept.mp4 52MB
  100. 43 - Deep Learning How to Build a Neural Network from Scratch with NumPy/298 - Basic NN Example Part 4.mp4 52MB
  101. 1 - Part 1 Introduction/2 - What Does the Course Cover.mp4 52MB
  102. 20 - Statistics Hypothesis Testing/126 - pvalue.mp4 52MB
  103. 64 - Appendix Working with Text Files in Python/497 - Importing Text Files with open.mp4 51MB
  104. 44 - Deep Learning TensorFlow 20 Introduction/305 - Outlining the Model with TensorFlow 2.mp4 51MB
  105. 38 - Advanced Statistical Methods KMeans Clustering/265 - How is Clustering Useful.mp4 51MB
  106. 12 - Probability Distributions/53 - Types of Probability Distributions.mp4 51MB
  107. 63 - Appendix pandas Fundamentals/484 - pandas DataFrames Common Attributes.mp4 51MB
  108. 20 - Statistics Hypothesis Testing/120 - Null vs Alternative Hypothesis.mp4 51MB
  109. 55 - Appendix Deep Learning TensorFlow 1 Business Case/397 - Business Case Optimization.mp4 51MB
  110. 64 - Appendix Working with Text Files in Python/512 - Saving Your Data with NumPy Part I npy.mp4 50MB
  111. 44 - Deep Learning TensorFlow 20 Introduction/306 - Interpreting the Result and Extracting the Weights and Bias.mp4 50MB
  112. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/455 - Saving the Model and Preparing it for Deployment.mp4 50MB
  113. 64 - Appendix Working with Text Files in Python/496 - Importing Text Files open.mp4 50MB
  114. 40 - Part 6 Mathematics/276 - Addition and Subtraction of Matrices.mp4 50MB
  115. 62 - Appendix Additional Python Tools/473 - List Comprehensions.mp4 49MB
  116. 37 - Advanced Statistical Methods Cluster Analysis/250 - Some Examples of Clusters.mp4 49MB
  117. 18 - Statistics Inferential Statistics Confidence Intervals/110 - Margin of Error.mp4 49MB
  118. 13 - Probability Probability in Other Fields/68 - Probability in Statistics.mp4 49MB
  119. 52 - Deep Learning Conclusion/366 - An overview of CNNs.mp4 48MB
  120. 15 - Statistics Descriptive Statistics/81 - Mean median and mode.mp4 48MB
  121. 20 - Statistics Hypothesis Testing/133 - Test for the mean Independent Samples Part 2.mp4 47MB
  122. 64 - Appendix Working with Text Files in Python/509 - Importing Data with the squeeze Method.mp4 46MB
  123. 9 - Part 2 Probability/25 - The Basic Probability Formula.mp4 46MB
  124. 62 - Appendix Additional Python Tools/469 - Using the format Method.mp4 45MB
  125. 32 - Advanced Statistical Methods Linear Regression with StatsModels/184 - Python Packages Installation.mp4 45MB
  126. 15 - Statistics Descriptive Statistics/72 - Levels of Measurement.mp4 45MB
  127. 12 - Probability Distributions/57 - Discrete Distributions The Binomial Distribution.mp4 44MB
  128. 15 - Statistics Descriptive Statistics/85 - Variance.mp4 44MB
  129. 50 - Deep Learning Classifying on the MNIST Dataset/342 - MNIST Preprocess the Data Create a Validation Set and Scale It.mp4 44MB
  130. 18 - Statistics Inferential Statistics Confidence Intervals/103 - What are Confidence Intervals.mp4 44MB
  131. 50 - Deep Learning Classifying on the MNIST Dataset/350 - MNIST Testing the Model.mp4 43MB
  132. 5 - The Field of Data Science Popular Data Science Techniques/18 - Real Life Examples of Traditional Methods.mp4 43MB
  133. 36 - Advanced Statistical Methods Logistic Regression/234 - A Simple Example in Python.mp4 43MB
  134. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/311 - Digging into a Deep Net.mp4 42MB
  135. 34 - Advanced Statistical Methods Linear Regression with sklearn/208 - Simple Linear Regression with sklearn A StatsModelslike Summary Table.mp4 42MB
  136. 40 - Part 6 Mathematics/278 - Transpose of a Matrix.mp4 42MB
  137. 17 - Statistics Inferential Statistics Fundamentals/102 - Estimators and Estimates.mp4 42MB
  138. 62 - Appendix Additional Python Tools/474 - Anonymous Lambda Functions.mp4 41MB
  139. 36 - Advanced Statistical Methods Logistic Regression/235 - Logistic vs Logit Function.mp4 41MB
  140. 50 - Deep Learning Classifying on the MNIST Dataset/346 - MNIST Outline the Model.mp4 41MB
  141. 58 - Case Study Preprocessing the Absenteeismdata/411 - Importing the Absenteeism Data in Python.mp4 41MB
  142. 36 - Advanced Statistical Methods Logistic Regression/247 - Testing the Model.mp4 41MB
  143. 34 - Advanced Statistical Methods Linear Regression with sklearn/220 - Predicting with the Standardized Coefficients.mp4 41MB
  144. 28 - Python Sequences/166 - Lists.mp4 41MB
  145. 63 - Appendix pandas Fundamentals/487 - pandas DataFrames Indexing with loc.mp4 41MB
  146. 58 - Case Study Preprocessing the Absenteeismdata/441 - Final Remarks of this Section.mp4 41MB
  147. 63 - Appendix pandas Fundamentals/479 - Parameters and Arguments in pandas.mp4 41MB
  148. 5 - The Field of Data Science Popular Data Science Techniques/16 - Real Life Examples of Business Intelligence BI.mp4 41MB
  149. 64 - Appendix Working with Text Files in Python/514 - Saving Your Data with NumPy Part III csv.mp4 41MB
  150. 64 - Appendix Working with Text Files in Python/511 - Saving Your Data with pandas.mp4 41MB
  151. 34 - Advanced Statistical Methods Linear Regression with sklearn/212 - Calculating the Adjusted RSquared in sklearn.mp4 41MB
  152. 15 - Statistics Descriptive Statistics/91 - Correlation Coefficient.mp4 40MB
  153. 60 - Case Study Loading the absenteeismmodule/460 - Deploying the absenteeismmodule Part I.mp4 39MB
  154. 34 - Advanced Statistical Methods Linear Regression with sklearn/214 - Feature Selection Fregression.mp4 39MB
  155. 13 - Probability Probability in Other Fields/69 - Probability in Data Science.mp4 39MB
  156. 29 - Python Iterations/171 - While Loops and Incrementing.mp4 39MB
  157. 23 - Python Variables and Data Types/145 - Python Strings.mp4 39MB
  158. 63 - Appendix pandas Fundamentals/475 - Introduction to pandas Series.mp4 38MB
  159. 64 - Appendix Working with Text Files in Python/510 - Importing Files in Jupyter.mp4 38MB
  160. 29 - Python Iterations/172 - Lists with the range Function.mp4 38MB
  161. 58 - Case Study Preprocessing the Absenteeismdata/437 - Extracting the Day of the Week from the Date Column.mp4 38MB
  162. 36 - Advanced Statistical Methods Logistic Regression/244 - Calculating the Accuracy of the Model.mp4 38MB
  163. 36 - Advanced Statistical Methods Logistic Regression/238 - An Invaluable Coding Tip.mp4 38MB
  164. 25 - Python Other Python Operators/154 - Logical and Identity Operators.mp4 37MB
  165. 40 - Part 6 Mathematics/274 - Arrays in Python A Convenient Way To Represent Matrices.mp4 37MB
  166. 50 - Deep Learning Classifying on the MNIST Dataset/344 - MNIST Preprocess the Data Shuffle and Batch.mp4 37MB
  167. 22 - Part 4 Introduction to Python/142 - Prerequisites for Coding in the Jupyter Notebooks.mp4 37MB
  168. 15 - Statistics Descriptive Statistics/87 - Standard Deviation and Coefficient of Variation.mp4 37MB
  169. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/312 - NonLinearities and their Purpose.mp4 37MB
  170. 9 - Part 2 Probability/28 - Events and Their Complements.mp4 36MB
  171. 51 - Deep Learning Business Case Example/353 - Business Case Balancing the Dataset.mp4 36MB
  172. 55 - Appendix Deep Learning TensorFlow 1 Business Case/392 - The Importance of Working with a Balanced Dataset.mp4 36MB
  173. 20 - Statistics Hypothesis Testing/127 - Test for the Mean Population Variance Unknown.mp4 36MB
  174. 17 - Statistics Inferential Statistics Fundamentals/100 - Central Limit Theorem.mp4 36MB
  175. 55 - Appendix Deep Learning TensorFlow 1 Business Case/398 - Business Case Interpretation.mp4 36MB
  176. 15 - Statistics Descriptive Statistics/89 - Covariance.mp4 36MB
  177. 58 - Case Study Preprocessing the Absenteeismdata/440 - Working on Education Children and Pets.mp4 36MB
  178. 15 - Statistics Descriptive Statistics/79 - Cross Tables and Scatter Plots.mp4 36MB
  179. 11 - Probability Bayesian Inference/43 - Union of Sets.mp4 35MB
  180. 12 - Probability Distributions/58 - Discrete Distributions The Poisson Distribution.mp4 35MB
  181. 10 - Probability Combinatorics/34 - Solving Combinations.mp4 35MB
  182. 61 - Case Study Analyzing the Predicted Outputs in Tableau/468 - Analyzing Transportation Expense vs Probability in Tableau.mp4 35MB
  183. 63 - Appendix pandas Fundamentals/477 - Working with Methods in Python Part I.mp4 35MB
  184. 57 - Case Study Whats Next in the Course/409 - Introducing the Data Set.mp4 35MB
  185. 58 - Case Study Preprocessing the Absenteeismdata/435 - Analyzing the Dates from the Initial Data Set.mp4 35MB
  186. 56 - Software Integration/405 - Communication between Software Products through Text Files.mp4 34MB
  187. 58 - Case Study Preprocessing the Absenteeismdata/413 - Introduction to Terms with Multiple Meanings.mp4 34MB
  188. 39 - Advanced Statistical Methods Other Types of Clustering/270 - Heatmaps.mp4 34MB
  189. 58 - Case Study Preprocessing the Absenteeismdata/432 - Creating Checkpoints while Coding in Jupyter.mp4 34MB
  190. 15 - Statistics Descriptive Statistics/75 - Numerical Variables Frequency Distribution Table.mp4 34MB
  191. 40 - Part 6 Mathematics/275 - What is a Tensor.mp4 33MB
  192. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/384 - Calculating the Accuracy of the Model.mp4 33MB
  193. 64 - Appendix Working with Text Files in Python/513 - Saving Your Data with NumPy Part II npz.mp4 32MB
  194. 42 - Deep Learning Introduction to Neural Networks/293 - Optimization Algorithm 1Parameter Gradient Descent.mp4 32MB
  195. 55 - Appendix Deep Learning TensorFlow 1 Business Case/400 - Business Case A Comment on the Homework.mp4 32MB
  196. 36 - Advanced Statistical Methods Logistic Regression/242 - Binary Predictors in a Logistic Regression.mp4 32MB
  197. 28 - Python Sequences/168 - Tuples.mp4 32MB
  198. 11 - Probability Bayesian Inference/50 - Bayes Law.mp4 32MB
  199. 34 - Advanced Statistical Methods Linear Regression with sklearn/218 - Feature Scaling Standardization.mp4 32MB
  200. 44 - Deep Learning TensorFlow 20 Introduction/307 - Customizing a TensorFlow 2 Model.mp4 32MB
  201. 56 - Software Integration/402 - What are Data Servers Clients Requests and Responses.mp4 31MB
  202. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/204 - Making Predictions with the Linear Regression.mp4 31MB
  203. 63 - Appendix pandas Fundamentals/483 - Introduction to pandas DataFrames Part II.mp4 31MB
  204. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/383 - MNIST Loss and Optimization Algorithm.mp4 30MB
  205. 12 - Probability Distributions/52 - Fundamentals of Probability Distributions.mp4 30MB
  206. 12 - Probability Distributions/60 - Continuous Distributions The Normal Distribution.mp4 30MB
  207. 20 - Statistics Hypothesis Testing/124 - Test for the Mean Population Variance Known.mp4 30MB
  208. 12 - Probability Distributions/61 - Continuous Distributions The Standard Normal Distribution.mp4 30MB
  209. 57 - Case Study Whats Next in the Course/407 - Game Plan for this Python SQL and Tableau Business Exercise.mp4 30MB
  210. 11 - Probability Bayesian Inference/41 - Ways Sets Can Interact.mp4 30MB
  211. 43 - Deep Learning How to Build a Neural Network from Scratch with NumPy/297 - Basic NN Example Part 3.mp4 29MB
  212. 2 - The Field of Data Science The Various Data Science Disciplines/6 - Business Analytics Data Analytics and Data Science An Introduction.mp4 29MB
  213. 53 - Appendix Deep Learning TensorFlow 1 Introduction/375 - Basic NN Example with TF Inputs Outputs Targets Weights Biases.mp4 29MB
  214. 64 - Appendix Working with Text Files in Python/507 - Working with Excel xlsx Data.mp4 29MB
  215. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/446 - Standardizing the Data.mp4 29MB
  216. 53 - Appendix Deep Learning TensorFlow 1 Introduction/377 - Basic NN Example with TF Model Output.mp4 28MB
  217. 20 - Statistics Hypothesis Testing/131 - Test for the mean Independent Samples Part 1.mp4 28MB
  218. 29 - Python Iterations/175 - How to Iterate over Dictionaries.mp4 28MB
  219. 11 - Probability Bayesian Inference/46 - The Conditional Probability Formula.mp4 28MB
  220. 63 - Appendix pandas Fundamentals/481 - Using sortvalues.mp4 27MB
  221. 53 - Appendix Deep Learning TensorFlow 1 Introduction/376 - Basic NN Example with TF Loss Function and Gradient Descent.mp4 27MB
  222. 11 - Probability Bayesian Inference/40 - Sets and Events.mp4 27MB
  223. 28 - Python Sequences/167 - List Slicing.mp4 27MB
  224. 18 - Statistics Inferential Statistics Confidence Intervals/106 - Confidence Interval Clarifications.mp4 27MB
  225. 17 - Statistics Inferential Statistics Fundamentals/96 - What is a Distribution.mp4 27MB
  226. 5 - The Field of Data Science Popular Data Science Techniques/21 - Real Life Examples of Machine Learning ML.mp4 27MB
  227. 15 - Statistics Descriptive Statistics/83 - Skewness.mp4 27MB
  228. 10 - Probability Combinatorics/30 - Permutations and How to Use Them.mp4 26MB
  229. 5 - The Field of Data Science Popular Data Science Techniques/12 - Real Life Examples of Traditional Data.mp4 26MB
  230. 58 - Case Study Preprocessing the Absenteeismdata/439 - Analyzing Several Straightforward Columns for this Exercise.mp4 26MB
  231. 29 - Python Iterations/173 - Conditional Statements and Loops.mp4 26MB
  232. 10 - Probability Combinatorics/37 - Combinatorics in RealLife The Lottery.mp4 26MB
  233. 26 - Python Conditional Statements/157 - The ELIF Statement.mp4 26MB
  234. 43 - Deep Learning How to Build a Neural Network from Scratch with NumPy/296 - Basic NN Example Part 2.mp4 25MB
  235. 20 - Statistics Hypothesis Testing/123 - Type I Error and Type II Error.mp4 25MB
  236. 11 - Probability Bayesian Inference/49 - The Multiplication Law.mp4 25MB
  237. 12 - Probability Distributions/65 - Continuous Distributions The Logistic Distribution.mp4 25MB
  238. 18 - Statistics Inferential Statistics Confidence Intervals/115 - Confidence intervals Two means Independent Samples Part 2.mp4 25MB
  239. 64 - Appendix Working with Text Files in Python/492 - Importing Data in Python Principles.mp4 25MB
  240. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/330 - Learning Rate Schedules or How to Choose the Optimal Learning Rate.mp4 25MB
  241. 40 - Part 6 Mathematics/279 - Dot Product.mp4 25MB
  242. 12 - Probability Distributions/64 - Continuous Distributions The Exponential Distribution.mp4 24MB
  243. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/452 - Interpreting the Coefficients of the Logistic Regression.mp4 24MB
  244. 39 - Advanced Statistical Methods Other Types of Clustering/269 - Dendrogram.mp4 24MB
  245. 18 - Statistics Inferential Statistics Confidence Intervals/108 - Confidence Intervals Population Variance Unknown Tscore.mp4 24MB
  246. 36 - Advanced Statistical Methods Logistic Regression/239 - Understanding Logistic Regression Tables.mp4 24MB
  247. 53 - Appendix Deep Learning TensorFlow 1 Introduction/372 - TensorFlow Intro.mp4 24MB
  248. 2 - The Field of Data Science The Various Data Science Disciplines/4 - Data Science and Business Buzzwords Why are there so Many.mp4 24MB
  249. 10 - Probability Combinatorics/38 - A Recap of Combinatorics.mp4 23MB
  250. 50 - Deep Learning Classifying on the MNIST Dataset/341 - MNIST Importing the Relevant Packages and Loading the Data.mp4 23MB
  251. 46 - Deep Learning Overfitting/319 - Underfitting and Overfitting for Classification.mp4 23MB
  252. 64 - Appendix Working with Text Files in Python/499 - Importing csv Files Part II.mp4 23MB
  253. 22 - Part 4 Introduction to Python/137 - Introduction to Programming.mp4 23MB
  254. 62 - Appendix Additional Python Tools/470 - Iterating Over Range Objects.mp4 23MB
  255. 42 - Deep Learning Introduction to Neural Networks/294 - Optimization Algorithm nParameter Gradient Descent.mp4 22MB
  256. 42 - Deep Learning Introduction to Neural Networks/288 - The Linear model with Multiple Inputs and Multiple Outputs.mp4 22MB
  257. 11 - Probability Bayesian Inference/47 - The Law of Total Probability.mp4 22MB
  258. 44 - Deep Learning TensorFlow 20 Introduction/301 - TensorFlow Outline and Comparison with Other Libraries.mp4 22MB
  259. 40 - Part 6 Mathematics/273 - Linear Algebra and Geometry.mp4 21MB
  260. 11 - Probability Bayesian Inference/45 - Dependence and Independence of Sets.mp4 21MB
  261. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/381 - MNIST Relevant Packages.mp4 21MB
  262. 52 - Deep Learning Conclusion/368 - An Overview of nonNN Approaches.mp4 21MB
  263. 29 - Python Iterations/170 - For Loops.mp4 21MB
  264. 62 - Appendix Additional Python Tools/471 - Introduction to Nested For Loops.mp4 21MB
  265. 32 - Advanced Statistical Methods Linear Regression with StatsModels/181 - The Linear Regression Model.mp4 21MB
  266. 12 - Probability Distributions/56 - Discrete Distributions The Bernoulli Distribution.mp4 21MB
  267. 37 - Advanced Statistical Methods Cluster Analysis/249 - Introduction to Cluster Analysis.mp4 21MB
  268. 10 - Probability Combinatorics/35 - Symmetry of Combinations.mp4 21MB
  269. 18 - Statistics Inferential Statistics Confidence Intervals/107 - Students T Distribution.mp4 21MB
  270. 64 - Appendix Working with Text Files in Python/501 - Importing Data with indexcol.mp4 21MB
  271. 44 - Deep Learning TensorFlow 20 Introduction/302 - TensorFlow 1 vs TensorFlow 2.mp4 20MB
  272. 10 - Probability Combinatorics/32 - Solving Variations with Repetition.mp4 20MB
  273. 50 - Deep Learning Classifying on the MNIST Dataset/347 - MNIST Select the Loss and the Optimizer.mp4 20MB
  274. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/443 - Exploring the Problem with a Machine Learning Mindset.mp4 20MB
  275. 10 - Probability Combinatorics/36 - Solving Combinations with Separate Sample Spaces.mp4 20MB
  276. 58 - Case Study Preprocessing the Absenteeismdata/429 - Reordering Columns in a Pandas DataFrame in Python.mp4 20MB
  277. 42 - Deep Learning Introduction to Neural Networks/285 - Types of Machine Learning.mp4 19MB
  278. 34 - Advanced Statistical Methods Linear Regression with sklearn/211 - Multiple Linear Regression with sklearn.mp4 19MB
  279. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/385 - MNIST Batching and Early Stopping.mp4 19MB
  280. 22 - Part 4 Introduction to Python/138 - Why Python.mp4 19MB
  281. 15 - Statistics Descriptive Statistics/77 - The Histogram.mp4 19MB
  282. 41 - Part 7 Deep Learning/282 - What to Expect from this Part.mp4 18MB
  283. 51 - Deep Learning Business Case Example/356 - Business Case Load the Preprocessed Data.mp4 18MB
  284. 18 - Statistics Inferential Statistics Confidence Intervals/113 - Confidence intervals Two means Independent Samples Part 1.mp4 18MB
  285. 57 - Case Study Whats Next in the Course/408 - The Business Task.mp4 18MB
  286. 35 - Advanced Statistical Methods Practical Example Linear Regression/227 - Practical Example Linear Regression Part 3.mp4 18MB
  287. 38 - Advanced Statistical Methods KMeans Clustering/256 - Clustering Categorical Data.mp4 18MB
  288. 64 - Appendix Working with Text Files in Python/493 - Plain Text Files Flat Files and More.mp4 18MB
  289. 58 - Case Study Preprocessing the Absenteeismdata/415 - Using a Statistical Approach towards the Solution to the Exercise.mp4 18MB
  290. 53 - Appendix Deep Learning TensorFlow 1 Introduction/373 - Actual Introduction to TensorFlow.mp4 18MB
  291. 36 - Advanced Statistical Methods Logistic Regression/241 - What do the Odds Actually Mean.mp4 18MB
  292. 5 - The Field of Data Science Popular Data Science Techniques/14 - Real Life Examples of Big Data.mp4 17MB
  293. 27 - Python Python Functions/165 - Builtin Functions in Python.mp4 17MB
  294. 49 - Deep Learning Preprocessing/336 - Standardization.mp4 17MB
  295. 30 - Python Advanced Python Tools/179 - Importing Modules in Python.mp4 17MB
  296. 11 - Probability Bayesian Inference/48 - The Additive Rule.mp4 17MB
  297. 63 - Appendix pandas Fundamentals/482 - Introduction to pandas DataFrames Part I.mp4 17MB
  298. 10 - Probability Combinatorics/33 - Solving Variations without Repetition.mp4 17MB
  299. 64 - Appendix Working with Text Files in Python/490 - Structured SemiStructured and Unstructured Data.mp4 17MB
  300. 40 - Part 6 Mathematics/271 - What is a Matrix.mp4 17MB
  301. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/310 - What is a Deep Net.mp4 17MB
  302. 11 - Probability Bayesian Inference/42 - Intersection of Sets.mp4 16MB
  303. 64 - Appendix Working with Text Files in Python/488 - An Introduction to Working with Files in Python.mp4 16MB
  304. 38 - Advanced Statistical Methods KMeans Clustering/261 - To Standardize or not to Standardize.mp4 16MB
  305. 32 - Advanced Statistical Methods Linear Regression with StatsModels/191 - RSquared.mp4 16MB
  306. 12 - Probability Distributions/63 - Continuous Distributions The ChiSquared Distribution.mp4 16MB
  307. 2 - The Field of Data Science The Various Data Science Disciplines/5 - What is the difference between Analysis and Analytics.mp4 16MB
  308. 51 - Deep Learning Business Case Example/361 - Business Case Testing the Model.mp4 16MB
  309. 23 - Python Variables and Data Types/143 - Variables.mp4 16MB
  310. 38 - Advanced Statistical Methods KMeans Clustering/253 - KMeans Clustering.mp4 16MB
  311. 65 - Bonus Lecture/517 - 365-Data-Science-Data-Science-Interview-Questions-Guide.pdf 16MB
  312. 64 - Appendix Working with Text Files in Python/491 - Text Files and Data Connectivity.mp4 16MB
  313. 63 - Appendix pandas Fundamentals/478 - Working with Methods in Python Part II.mp4 15MB
  314. 11 - Probability Bayesian Inference/44 - Mutually Exclusive Sets.mp4 15MB
  315. 46 - Deep Learning Overfitting/318 - What is Overfitting.mp4 15MB
  316. 53 - Appendix Deep Learning TensorFlow 1 Introduction/374 - Types of File Formats supporting Tensors.mp4 15MB
  317. 43 - Deep Learning How to Build a Neural Network from Scratch with NumPy/295 - Basic NN Example Part 1.mp4 15MB
  318. 12 - Probability Distributions/55 - Discrete Distributions The Uniform Distribution.mp4 15MB
  319. 46 - Deep Learning Overfitting/323 - Early Stopping or When to Stop Training.mp4 15MB
  320. 24 - Python Basic Python Syntax/146 - Using Arithmetic Operators in Python.mp4 15MB
  321. 59 - Case Study Applying Machine Learning to Create the absenteeismmodule/445 - Selecting the Inputs for the Logistic Regression.mp4 15MB
  322. 44 - Deep Learning TensorFlow 20 Introduction/304 - Types of File Formats Supporting TensorFlow.mp4 15MB
  323. 34 - Advanced Statistical Methods Linear Regression with sklearn/205 - What is sklearn and How is it Different from Other Packages.mp4 15MB
  324. 38 - Advanced Statistical Methods KMeans Clustering/260 - Pros and Cons of KMeans Clustering.mp4 15MB
  325. 36 - Advanced Statistical Methods Logistic Regression/236 - Building a Logistic Regression.mp4 15MB
  326. 10 - Probability Combinatorics/31 - Simple Operations with Factorials.mp4 15MB
  327. 42 - Deep Learning Introduction to Neural Networks/283 - Introduction to Neural Networks.mp4 14MB
  328. 46 - Deep Learning Overfitting/321 - Training Validation and Test Datasets.mp4 14MB
  329. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/327 - Stochastic Gradient Descent.mp4 14MB
  330. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/315 - Backpropagation.mp4 14MB
  331. 27 - Python Python Functions/160 - How to Create a Function with a Parameter.mp4 14MB
  332. 52 - Deep Learning Conclusion/363 - Summary on What Youve Learned.mp4 14MB
  333. 32 - Advanced Statistical Methods Linear Regression with StatsModels/187 - Using Seaborn for Graphs.mp4 14MB
  334. 12 - Probability Distributions/62 - Continuous Distributions The Students T Distribution.mp4 14MB
  335. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/198 - A2 No Endogeneity.mp4 14MB
  336. 32 - Advanced Statistical Methods Linear Regression with StatsModels/189 - Decomposition of Variability.mp4 14MB
  337. 12 - Probability Distributions/54 - Characteristics of Discrete Distributions.mp4 14MB
  338. 17 - Statistics Inferential Statistics Fundamentals/98 - The Standard Normal Distribution.mp4 14MB
  339. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/314 - Activation Functions Softmax Activation.mp4 14MB
  340. 39 - Advanced Statistical Methods Other Types of Clustering/268 - Types of Clustering.mp4 14MB
  341. 64 - Appendix Working with Text Files in Python/495 - Common Naming Conventions.mp4 14MB
  342. 42 - Deep Learning Introduction to Neural Networks/292 - Common Objective Functions CrossEntropy Loss.mp4 14MB
  343. 46 - Deep Learning Overfitting/320 - What is Validation.mp4 13MB
  344. 47 - Deep Learning Initialization/324 - What is Initialization.mp4 13MB
  345. 37 - Advanced Statistical Methods Cluster Analysis/251 - Difference between Classification and Clustering.mp4 13MB
  346. 40 - Part 6 Mathematics/272 - Scalars and Vectors.mp4 13MB
  347. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/313 - Activation Functions.mp4 13MB
  348. 64 - Appendix Working with Text Files in Python/489 - File vs File Object Reading vs Parsing Data.mp4 13MB
  349. 50 - Deep Learning Classifying on the MNIST Dataset/340 - MNIST How to Tackle the MNIST.mp4 13MB
  350. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/332 - Adaptive Learning Rate Schedules AdaGrad and RMSprop.mp4 13MB
  351. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/380 - MNIST How to Tackle the MNIST.mp4 12MB
  352. 22 - Part 4 Introduction to Python/139 - Why Jupyter.mp4 12MB
  353. 49 - Deep Learning Preprocessing/334 - Preprocessing Introduction.mp4 12MB
  354. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/316 - Backpropagation Picture.mp4 12MB
  355. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/200 - A4 No Autocorrelation.mp4 12MB
  356. 30 - Python Advanced Python Tools/176 - Object Oriented Programming.mp4 12MB
  357. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/195 - Test for Significance of the Model FTest.mp4 12MB
  358. 27 - Python Python Functions/161 - Defining a Function in Python Part II.mp4 12MB
  359. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/201 - A5 No Multicollinearity.mp4 11MB
  360. 49 - Deep Learning Preprocessing/338 - Binary and OneHot Encoding.mp4 11MB
  361. 18 - Statistics Inferential Statistics Confidence Intervals/117 - Confidence intervals Two means Independent Samples Part 3.mp4 11MB
  362. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/333 - Adam Adaptive Moment Estimation.mp4 11MB
  363. 42 - Deep Learning Introduction to Neural Networks/289 - Graphical Representation of Simple Neural Networks.mp4 11MB
  364. 34 - Advanced Statistical Methods Linear Regression with sklearn/216 - Creating a Summary Table with Pvalues.mp4 11MB
  365. 52 - Deep Learning Conclusion/367 - An Overview of RNNs.mp4 11MB
  366. 36 - Advanced Statistical Methods Logistic Regression/246 - Underfitting and Overfitting.mp4 11MB
  367. 42 - Deep Learning Introduction to Neural Networks/286 - The Linear Model Linear Algebraic Version.mp4 11MB
  368. 42 - Deep Learning Introduction to Neural Networks/287 - The Linear Model with Multiple Inputs.mp4 10MB
  369. 42 - Deep Learning Introduction to Neural Networks/284 - Training the Model.mp4 10MB
  370. 36 - Advanced Statistical Methods Logistic Regression/233 - Introduction to Logistic Regression.mp4 10MB
  371. 23 - Python Variables and Data Types/144 - Numbers and Boolean Values in Python.mp4 10MB
  372. 58 - Case Study Preprocessing the Absenteeismdata/424 - More on Dummy Variables A Statistical Perspective.mp4 10MB
  373. 17 - Statistics Inferential Statistics Fundamentals/101 - Standard error.mp4 10MB
  374. 27 - Python Python Functions/163 - Conditional Statements and Functions.mp4 10MB
  375. 40 - Part 6 Mathematics/277 - Errors when Adding Matrices.mp4 10MB
  376. 10 - Probability Combinatorics/29 - Fundamentals of Combinatorics.mp4 9MB
  377. 22 - Part 4 Introduction to Python/141 - Understanding Jupyters Interface the Notebook Dashboard.mp4 9MB
  378. 46 - Deep Learning Overfitting/322 - NFold Cross Validation.mp4 9MB
  379. 53 - Appendix Deep Learning TensorFlow 1 Introduction/370 - How to Install TensorFlow 1.mp4 9MB
  380. 47 - Deep Learning Initialization/325 - Types of Simple Initializations.mp4 9MB
  381. 26 - Python Conditional Statements/156 - The ELSE Statement.mp4 9MB
  382. 26 - Python Conditional Statements/155 - The IF Statement.mp4 9MB
  383. 44 - Deep Learning TensorFlow 20 Introduction/303 - A Note on TensorFlow 2 Syntax.mp4 9MB
  384. 12 - Probability Distributions/66 - FIFA19-post.csv 9MB
  385. 12 - Probability Distributions/66 - FIFA19.csv 9MB
  386. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/192 - Multiple Linear Regression.mp4 8MB
  387. 42 - Deep Learning Introduction to Neural Networks/290 - What is the Objective Function.mp4 8MB
  388. 47 - Deep Learning Initialization/326 - StateoftheArt Method Xavier Glorot Initialization.mp4 8MB
  389. 34 - Advanced Statistical Methods Linear Regression with sklearn/222 - Underfitting and Overfitting.mp4 8MB
  390. 42 - Deep Learning Introduction to Neural Networks/291 - Common Objective Functions L2norm Loss.mp4 8MB
  391. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/309 - What is a Layer.mp4 8MB
  392. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/196 - OLS Assumptions.mp4 8MB
  393. 58 - Case Study Preprocessing the Absenteeismdata/438 - Absenteeism-Exercise-Preprocessing-LECTURES.ipynb 8MB
  394. 34 - Advanced Statistical Methods Linear Regression with sklearn/206 - How are we Going to Approach this Section.mp4 8MB
  395. 64 - Appendix Working with Text Files in Python/494 - Text Files of Fixed Width.mp4 7MB
  396. 55 - Appendix Deep Learning TensorFlow 1 Business Case/399 - Business Case Testing the Model.mp4 7MB
  397. 37 - Advanced Statistical Methods Cluster Analysis/252 - Math Prerequisites.mp4 7MB
  398. 49 - Deep Learning Preprocessing/337 - Preprocessing Categorical Data.mp4 7MB
  399. 30 - Python Advanced Python Tools/178 - What is the Standard Library.mp4 7MB
  400. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/329 - Momentum.mp4 7MB
  401. 54 - Appendix Deep Learning TensorFlow 1 Classifying on the MNIST Dataset/379 - MNIST What is the MNIST Dataset.mp4 7MB
  402. 2 - The Field of Data Science The Various Data Science Disciplines/7 - 365-DataScience.png 7MB
  403. 2 - The Field of Data Science The Various Data Science Disciplines/8 - 365-DataScience.png 7MB
  404. 26 - Python Conditional Statements/158 - A Note on Boolean Values.mp4 7MB
  405. 52 - Deep Learning Conclusion/364 - Whats Further out there in terms of Machine Learning.mp4 7MB
  406. 50 - Deep Learning Classifying on the MNIST Dataset/339 - MNIST The Dataset.mp4 7MB
  407. 25 - Python Other Python Operators/153 - Comparison Operators.mp4 7MB
  408. 29 - Python Iterations/174 - Conditional Statements Functions and Loops.mp4 7MB
  409. 55 - Appendix Deep Learning TensorFlow 1 Business Case/391 - Business Case Outlining the Solution.mp4 6MB
  410. 32 - Advanced Statistical Methods Linear Regression with StatsModels/182 - Correlation vs Regression.mp4 6MB
  411. 31 - Part 5 Advanced Statistical Methods in Python/180 - Introduction to Regression Analysis.mp4 6MB
  412. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/328 - Problems with Gradient Descent.mp4 5MB
  413. 38 - Advanced Statistical Methods KMeans Clustering/262 - Relationship between Clustering and Regression.mp4 5MB
  414. 17 - Statistics Inferential Statistics Fundamentals/95 - Introduction.mp4 5MB
  415. 27 - Python Python Functions/159 - Defining a Function in Python.mp4 5MB
  416. 27 - Python Python Functions/162 - How to Use a Function within a Function.mp4 5MB
  417. 33 - Advanced Statistical Methods Multiple Linear Regression with StatsModels/197 - A1 Linearity.mp4 5MB
  418. 27 - Python Python Functions/164 - Functions Containing a Few Arguments.mp4 5MB
  419. 48 - Deep Learning Digging into Gradient Descent and Learning Rate Schedules/331 - Learning Rate Schedules Visualized.mp4 5MB
  420. 49 - Deep Learning Preprocessing/335 - Types of Basic Preprocessing.mp4 5MB
  421. 51 - Deep Learning Business Case Example/352 - Business Case Outlining the Solution.mp4 5MB
  422. 24 - Python Basic Python Syntax/152 - Structuring with Indentation.mp4 4MB
  423. 24 - Python Basic Python Syntax/147 - The Double Equality Sign.mp4 4MB
  424. 24 - Python Basic Python Syntax/149 - Add Comments.mp4 4MB
  425. 24 - Python Basic Python Syntax/151 - Indexing Elements.mp4 4MB
  426. 32 - Advanced Statistical Methods Linear Regression with StatsModels/183 - Geometrical Representation of the Linear Regression Model.mp4 3MB
  427. 30 - Python Advanced Python Tools/177 - Modules and Packages.mp4 3MB
  428. 64 - Appendix Working with Text Files in Python/516 - Working with Text Files in Python Conclusion.mp4 3MB
  429. 24 - Python Basic Python Syntax/148 - How to Reassign Values.mp4 3MB
  430. 22 - Part 4 Introduction to Python/137 - Introduction-to-Python-Course-Notes.pdf 2MB
  431. 23 - Python Variables and Data Types/143 - Introduction-to-Python-Course-Notes.pdf 2MB
  432. 19 - Statistics Practical Example Inferential Statistics/119 - 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx 2MB
  433. 24 - Python Basic Python Syntax/150 - Understanding Line Continuation.mp4 2MB
  434. 19 - Statistics Practical Example Inferential Statistics/118 - 3.17.Practical-example.Confidence-intervals-lesson.xlsx 2MB
  435. 19 - Statistics Practical Example Inferential Statistics/119 - 3.17.Practical-example.Confidence-intervals-exercise.xlsx 2MB
  436. 20 - Statistics Hypothesis Testing/126 - Online-p-value-calculator.pdf 1MB
  437. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/309 - Course-Notes-Section-6.pdf 936KB
  438. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/310 - Course-Notes-Section-6.pdf 936KB
  439. 11 - Probability Bayesian Inference/51 - CDS-2017-2018-Hamilton.pdf 845KB
  440. 35 - Advanced Statistical Methods Practical Example Linear Regression/231 - sklearn-Linear-Regression-Practical-Example-Part-5-with-comments.ipynb 711KB
  441. 51 - Deep Learning Business Case Example/351 - Audiobooks-data.csv 711KB
  442. 55 - Appendix Deep Learning TensorFlow 1 Business Case/390 - Audiobooks-data.csv 711KB
  443. 55 - Appendix Deep Learning TensorFlow 1 Business Case/392 - Audiobooks-data.csv 711KB
  444. 55 - Appendix Deep Learning TensorFlow 1 Business Case/393 - Audiobooks-data.csv 711KB
  445. 55 - Appendix Deep Learning TensorFlow 1 Business Case/394 - Audiobooks-data.csv 711KB
  446. 55 - Appendix Deep Learning TensorFlow 1 Business Case/400 - Audiobooks-data.csv 711KB
  447. 55 - Appendix Deep Learning TensorFlow 1 Business Case/401 - Audiobooks-data.csv 711KB
  448. 35 - Advanced Statistical Methods Practical Example Linear Regression/231 - sklearn-Linear-Regression-Practical-Example-Part-5.ipynb 698KB
  449. 20 - Statistics Hypothesis Testing/120 - Course-notes-hypothesis-testing.pdf 656KB
  450. 20 - Statistics Hypothesis Testing/122 - Course-notes-hypothesis-testing.pdf 656KB
  451. 64 - Appendix Working with Text Files in Python/488 - Common-Naming-Conventions.pdf 644KB
  452. 64 - Appendix Working with Text Files in Python/495 - Common-Naming-Conventions.pdf 644KB
  453. 43 - Deep Learning How to Build a Neural Network from Scratch with NumPy/295 - Shortcuts-for-Jupyter.pdf 619KB
  454. 44 - Deep Learning TensorFlow 20 Introduction/300 - Shortcuts-for-Jupyter.pdf 619KB
  455. 53 - Appendix Deep Learning TensorFlow 1 Introduction/373 - Shortcuts-for-Jupyter.pdf 619KB
  456. 42 - Deep Learning Introduction to Neural Networks/283 - Course-Notes-Section-2.pdf 578KB
  457. 42 - Deep Learning Introduction to Neural Networks/284 - Course-Notes-Section-2.pdf 578KB
  458. 14 - Part 3 Statistics/70 - Course-notes-descriptive-statistics.pdf 482KB
  459. 15 - Statistics Descriptive Statistics/71 - Course-notes-descriptive-statistics.pdf 482KB
  460. 12 - Probability Distributions/52 - Course-Notes-Probability-Distributions.pdf 464KB
  461. 35 - Advanced Statistical Methods Practical Example Linear Regression/229 - sklearn-Linear-Regression-Practical-Example-Part-4-with-comments.ipynb 408KB
  462. 35 - Advanced Statistical Methods Practical Example Linear Regression/229 - sklearn-Linear-Regression-Practical-Example-Part-4.ipynb 397KB
  463. 11 - Probability Bayesian Inference/40 - Course-Notes-Bayesian-Inference.pdf 386KB
  464. 17 - Statistics Inferential Statistics Fundamentals/95 - Course-notes-inferential-statistics.pdf 382KB
  465. 17 - Statistics Inferential Statistics Fundamentals/96 - Course-notes-inferential-statistics.pdf 382KB
  466. 9 - Part 2 Probability/25 - Course-Notes-Basic-Probability.pdf 371KB
  467. 35 - Advanced Statistical Methods Practical Example Linear Regression/228 - sklearn-Dummies-and-VIF-Exercise-Solution.ipynb 370KB
  468. 35 - Advanced Statistical Methods Practical Example Linear Regression/227 - sklearn-Linear-Regression-Practical-Example-Part-3-with-comments.ipynb 351KB
  469. 35 - Advanced Statistical Methods Practical Example Linear Regression/228 - sklearn-Dummies-and-VIF-Exercise.ipynb 345KB
  470. 12 - Probability Distributions/59 - Solving-Integrals.pdf 344KB
  471. 35 - Advanced Statistical Methods Practical Example Linear Regression/227 - sklearn-Linear-Regression-Practical-Example-Part-3.ipynb 344KB
  472. 35 - Advanced Statistical Methods Practical Example Linear Regression/225 - sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb 336KB
  473. 36 - Advanced Statistical Methods Logistic Regression/233 - Course-Notes-Logistic-Regression.pdf 335KB
  474. 36 - Advanced Statistical Methods Logistic Regression/234 - Course-Notes-Logistic-Regression.pdf 335KB
  475. 35 - Advanced Statistical Methods Practical Example Linear Regression/225 - sklearn-Linear-Regression-Practical-Example-Part-2.ipynb 329KB
  476. 2 - The Field of Data Science The Various Data Science Disciplines/6 - 365-DataScience-Diagram.pdf 323KB
  477. 2 - The Field of Data Science The Various Data Science Disciplines/7 - 365-DataScience-Diagram.pdf 323KB
  478. 13 - Probability Probability in Other Fields/69 - Probability-Cheat-Sheet.pdf 320KB
  479. 31 - Part 5 Advanced Statistical Methods in Python/180 - Course-notes-regression-analysis.pdf 312KB
  480. 32 - Advanced Statistical Methods Linear Regression with StatsModels/181 - Course-notes-regression-analysis.pdf 312KB
  481. 1 - Part 1 Introduction/3 - FAQ-The-Data-Science-Course.pdf 306KB
  482. 15 - Statistics Descriptive Statistics/74 - Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf 289KB
  483. 15 - Statistics Descriptive Statistics/78 - Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf 289KB
  484. 10 - Probability Combinatorics/39 - Additional-Exercises-Combinatorics-Solutions.pdf 246KB
  485. 10 - Probability Combinatorics/29 - Course-Notes-Combinatorics.pdf 226KB
  486. 35 - Advanced Statistical Methods Practical Example Linear Regression/224 - 1.04.Real-life-example.csv 220KB
  487. 35 - Advanced Statistical Methods Practical Example Linear Regression/225 - 1.04.Real-life-example.csv 220KB
  488. 35 - Advanced Statistical Methods Practical Example Linear Regression/228 - 1.04.Real-life-example.csv 220KB
  489. 35 - Advanced Statistical Methods Practical Example Linear Regression/229 - 1.04.Real-life-example.csv 220KB
  490. 35 - Advanced Statistical Methods Practical Example Linear Regression/231 - 1.04.Real-life-example.csv 220KB
  491. 64 - Appendix Working with Text Files in Python/505 - Lending-company.json 214KB
  492. 37 - Advanced Statistical Methods Cluster Analysis/249 - Course-Notes-Cluster-Analysis.pdf 209KB
  493. 37 - Advanced Statistical Methods Cluster Analysis/250 - Course-Notes-Cluster-Analysis.pdf 209KB
  494. 10 - Probability Combinatorics/34 - Combinations-With-Repetition.pdf 207KB
  495. 13 - Probability Probability in Other Fields/67 - Probability-in-Finance-Solutions.pdf 184KB
  496. 45 - Deep Learning Digging Deeper into NNs Introducing Deep Neural Networks/317 - Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf 182KB
  497. 35 - Advanced Statistical Methods Practical Example Linear Regression/224 - sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb 171KB
  498. 35 - Advanced Statistical Methods Practical Example Linear Regression/224 - sklearn-Linear-Regression-Practical-Example-Part-1.ipynb 167KB
  499. 63 - Appendix pandas Fundamentals/475 - Sales-products.csv 152KB
  500. 63 - Appendix pandas Fundamentals/487 - Sales-products.csv 152KB
  501. 16 - Statistics Practical Example Descriptive Statistics/93 - 2.13.Practical-example.Descriptive-statistics-lesson.xlsx 147KB
  502. 16 - Statistics Practical Example Descriptive Statistics/94 - 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx 146KB
  503. 12 - Probability Distributions/58 - Poisson-Expected-Value-and-Variance.pdf 146KB
  504. 12 - Probability Distributions/60 - Normal-Distribution-Exp-and-Var.pdf 144KB
  505. 58 - Case Study Preprocessing the Absenteeismdata/410 - data-preprocessing-homework.pdf 134KB
  506. 16 - Statistics Practical Example Descriptive Statistics/94 - 2.13.Practical-example.Descriptive-statistics-exercise.xlsx 120KB
  507. 63 - Appendix pandas Fundamentals/475 - pandas-Fundamentals-Solutions.ipynb 118KB
  508. 63 - Appendix pandas Fundamentals/487 - pandas-Fundamentals-Solutions.ipynb 118KB
  509. 64 - Appendix Working with Text Files in Python/498 - Lending-company-single-column-data.csv 114KB
  510. 63 - Appendix pandas Fundamentals/475 - Lending-company.csv 112KB
  511. 63 - Appendix pandas Fundamentals/487 - Lending-company.csv 112KB
  512. 64 - Appendix Working with Text Files in Python/498 - Lending-company.csv 112KB
  513. 36 - Advanced Statistical Methods Logistic Regression/248 - Testing-the-Model-Solution.ipynb 111KB
  514. 13 - Probability Probability in Other Fields/67 - Probability-in-Finance-Homework.pdf 111KB
  515. 10 - Probability Combinatorics/39 - Additional-Exercises-Combinatorics.pdf 107KB
  516. 64 - Appendix Working with Text Files in Python/507 - Lending-company.xlsx 93KB
  517. 10 - Probability Combinatorics/35 - Symmetry-Explained.pdf 85KB
  518. 44 - Deep Learning TensorFlow 20 Introduction/308 - TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb 84KB
  519. 43 - Deep Learning How to Build a Neural Network from Scratch with NumPy/299 - Minimal-example-Exercise-3.d.Solution.ipynb 84KB
  520. 44 - Deep Learning TensorFlow 20 Introduction/308 - TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb 84KB
  521. 44 - Deep Learning TensorFlow 20 Introduction/308 - TensorFlow-Minimal-example-All-exercises.ipynb 84KB
  522. 44 - Deep Learning TensorFlow 20 Introduction/307 - TensorFlow-Minimal-example-complete-with-comments.ipynb 8B