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GetFreeCourses.Co-Udemy-Complete 2022 Data Science & Machine Learning Bootcamp

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文件列表

  1. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1).mp4 230MB
  2. 12 - Serving a Tensorflow Model through a Website/014 Calculating the Centre of Mass and Shifting the Image.mp4 210MB
  3. 05 - Predict House Prices with Multivariable Linear Regression/031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module.mp4 201MB
  4. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix.mp4 193MB
  5. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate.mp4 190MB
  6. 03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports.mp4 187MB
  7. 12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server.mp4 175MB
  8. 05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques.mp4 175MB
  9. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions.mp4 174MB
  10. 11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout.mp4 174MB
  11. 12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas.mp4 173MB
  12. 12 - Serving a Tensorflow Model through a Website/010 Drawing on an HTML Canvas.mp4 159MB
  13. 12 - Serving a Tensorflow Model through a Website/016 Adding the Game Logic.mp4 158MB
  14. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques.mp4 153MB
  15. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/010 How to Create 3-Dimensional Charts.mp4 152MB
  16. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary.mp4 149MB
  17. 12 - Serving a Tensorflow Model through a Website/013 Resizing and Adding Padding to Images.mp4 148MB
  18. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn.mp4 146MB
  19. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2).mp4 145MB
  20. 03 - Python Programming for Data Science and Machine Learning/013 How to Make Sense of Python Documentation for Data Visualisation.mp4 138MB
  21. 12 - Serving a Tensorflow Model through a Website/006 HTML and CSS Styling.mp4 137MB
  22. 03 - Python Programming for Data Science and Machine Learning/014 Working with Python Objects to Analyse Data.mp4 135MB
  23. 12 - Serving a Tensorflow Model through a Website/012 Introduction to OpenCV.mp4 133MB
  24. 05 - Predict House Prices with Multivariable Linear Regression/027 Making Predictions (Part 1) MSE & R-Squared.mp4 127MB
  25. 03 - Python Programming for Data Science and Machine Learning/012 [Python] - Objects - Understanding Attributes and Methods.mp4 125MB
  26. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/002 Layers, Feature Generation and Learning.mp4 124MB
  27. 05 - Predict House Prices with Multivariable Linear Regression/023 Model Simplification & Baysian Information Criterion.mp4 120MB
  28. 11 - Use Tensorflow to Classify Handwritten Digits/006 Creating Tensors and Setting up the Neural Network Architecture.mp4 111MB
  29. 05 - Predict House Prices with Multivariable Linear Regression/011 Visualising Correlations with a Heatmap.mp4 108MB
  30. 05 - Predict House Prices with Multivariable Linear Regression/004 Clean and Explore the Data (Part 2) Find Missing Values.mp4 107MB
  31. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/013 [Python] - Loops and Performance Considerations.mp4 107MB
  32. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/028 Styling the Word Cloud with a Mask.mp4 106MB
  33. 05 - Predict House Prices with Multivariable Linear Regression/022 Understanding VIF & Testing for Multicollinearity.mp4 105MB
  34. 02 - Predict Movie Box Office Revenue with Linear Regression/003 Explore & Visualise the Data with Python.mp4 105MB
  35. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/002 Create a Full Matrix.mp4 105MB
  36. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/011 [Python] - Generator Functions & the yield Keyword.mp4 104MB
  37. 05 - Predict House Prices with Multivariable Linear Regression/007 Working with Index Data, Pandas Series, and Dummy Variables.mp4 104MB
  38. 12 - Serving a Tensorflow Model through a Website/002 Saving Tensorflow Models.mp4 104MB
  39. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/006 Making Predictions using InceptionResNet.mp4 103MB
  40. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/011 Understanding Partial Derivatives and How to use SymPy.mp4 103MB
  41. 05 - Predict House Prices with Multivariable Linear Regression/029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays.mp4 103MB
  42. 03 - Python Programming for Data Science and Machine Learning/007 [Python & Pandas] - Dataframes and Series.mp4 101MB
  43. 03 - Python Programming for Data Science and Machine Learning/010 [Python] - Functions - Part 2 Arguments & Parameters.mp4 99MB
  44. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/030 Styling Word Clouds with Custom Fonts.mp4 99MB
  45. 05 - Predict House Prices with Multivariable Linear Regression/026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals.mp4 99MB
  46. 11 - Use Tensorflow to Classify Handwritten Digits/009 Tensorboard Summaries and the Filewriter.mp4 99MB
  47. 12 - Serving a Tensorflow Model through a Website/015 Making a Prediction from a Digit drawn on the HTML Canvas.mp4 98MB
  48. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2).mp4 97MB
  49. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/002 Gathering Email Data and Working with Archives & Text Editors.mp4 96MB
  50. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/014 Reshaping and Slicing N-Dimensional Arrays.mp4 95MB
  51. 12 - Serving a Tensorflow Model through a Website/004 Converting a Model to Tensorflow.js.mp4 94MB
  52. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/006 [Python] - Loops and the Gradient Descent Algorithm.mp4 93MB
  53. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/019 Tokenizing, Removing Stop Words and the Python Set Data Structure.mp4 93MB
  54. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/035 Sparse Matrix (Part 2) Data Munging with Nested Loops.mp4 92MB
  55. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries.mp4 90MB
  56. 05 - Predict House Prices with Multivariable Linear Regression/030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2).mp4 90MB
  57. 11 - Use Tensorflow to Classify Handwritten Digits/010 Understanding the Tensorflow Graph Nodes and Edges.mp4 89MB
  58. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/006 Joint & Conditional Probability.mp4 88MB
  59. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/009 Reading Files (Part 2) Stream Objects and Email Structure.mp4 88MB
  60. 11 - Use Tensorflow to Classify Handwritten Digits/013 Prediction and Model Evaluation.mp4 87MB
  61. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/021 Removing HTML tags with BeautifulSoup.mp4 87MB
  62. 12 - Serving a Tensorflow Model through a Website/003 Loading a SavedModel.mp4 85MB
  63. 05 - Predict House Prices with Multivariable Linear Regression/012 Techniques to Style Scatter Plots.mp4 84MB
  64. 05 - Predict House Prices with Multivariable Linear Regression/010 Calculating Correlations and the Problem posed by Multicollinearity.mp4 83MB
  65. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/007 Coding Challenge Solution Using other Keras Models.mp4 82MB
  66. 05 - Predict House Prices with Multivariable Linear Regression/025 Residual Analysis (Part 1) Predicted vs Actual Values.mp4 81MB
  67. 05 - Predict House Prices with Multivariable Linear Regression/020 Improving the Model by Transforming the Data.mp4 81MB
  68. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/004 Exploring the CIFAR Data.mp4 81MB
  69. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/003 Costs and Disadvantages of Neural Networks.mp4 77MB
  70. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems.mp4 77MB
  71. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function.mp4 76MB
  72. 02 - Predict Movie Box Office Revenue with Linear Regression/005 Analyse and Evaluate the Results.mp4 75MB
  73. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/038 Checkpoint Understanding the Data.mp4 75MB
  74. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/021 Running Gradient Descent with a MSE Cost Function.mp4 74MB
  75. 11 - Use Tensorflow to Classify Handwritten Digits/008 TensorFlow Sessions and Batching Data.mp4 74MB
  76. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/031 Create the Vocabulary for the Spam Classifier.mp4 70MB
  77. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/016 Data Visualisation (Part 1) Pie Charts.mp4 70MB
  78. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/004 Preprocessing Image Data and How RGB Works.mp4 69MB
  79. 12 - Serving a Tensorflow Model through a Website/005 Introducing the Website Project and Tooling.mp4 69MB
  80. 03 - Python Programming for Data Science and Machine Learning/015 [Python] - Tips, Code Style and Naming Conventions.mp4 67MB
  81. 11 - Use Tensorflow to Classify Handwritten Digits/011 Name Scoping and Image Visualisation in Tensorboard.mp4 67MB
  82. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/012 Implementing Batch Gradient Descent with SymPy.mp4 65MB
  83. 05 - Predict House Prices with Multivariable Linear Regression/028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals.mp4 64MB
  84. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/003 Count the Tokens to Train the Naive Bayes Model.mp4 64MB
  85. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/005 Pre-processing Scaling Inputs and Creating a Validation Dataset.mp4 61MB
  86. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files.mp4 61MB
  87. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/005 Understanding the Power Rule & Creating Charts with Subplots.mp4 59MB
  88. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/034 Sparse Matrix (Part 1) Split the Training and Testing Data.mp4 58MB
  89. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/017 Transposing and Reshaping Arrays.mp4 58MB
  90. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/025 [Python] - Logical Operators to Create Subsets and Indices.mp4 57MB
  91. 05 - Predict House Prices with Multivariable Linear Regression/003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset.mp4 57MB
  92. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/024 Advanced Subsetting on DataFrames the apply() Function.mp4 55MB
  93. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/018 Implementing a MSE Cost Function.mp4 55MB
  94. 03 - Python Programming for Data Science and Machine Learning/011 [Python] - Functions - Part 3 Results & Return Values.mp4 54MB
  95. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/001 Setting up the Notebook and Understanding Delimiters in a Dataset.mp4 54MB
  96. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/007 Bayes Theorem.mp4 51MB
  97. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/026 Word Clouds & How to install Additional Python Packages.mp4 50MB
  98. 11 - Use Tensorflow to Classify Handwritten Digits/007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics.mp4 50MB
  99. 11 - Use Tensorflow to Classify Handwritten Digits/004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset.mp4 49MB
  100. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/005 Importing Keras Models and the Tensorflow Graph.mp4 49MB
  101. 05 - Predict House Prices with Multivariable Linear Regression/021 How to Interpret Coefficients using p-Values and Statistical Significance.mp4 49MB
  102. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/019 Understanding Nested Loops and Plotting the MSE Function (Part 1).mp4 49MB
  103. 05 - Predict House Prices with Multivariable Linear Regression/002 Gathering the Boston House Price Data.mp4 48MB
  104. 03 - Python Programming for Data Science and Machine Learning/005 [Python] - Variables and Types.mp4 48MB
  105. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/002 Joint Conditional Probability (Part 1) Dot Product.mp4 47MB
  106. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/004 LaTeX Markdown and Generating Data with Numpy.mp4 47MB
  107. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/029 Solving the Hamlet Challenge.mp4 47MB
  108. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/020 Word Stemming & Removing Punctuation.mp4 47MB
  109. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/014 Cleaning Data (Part 2) Working with a DataFrame Index.mp4 46MB
  110. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/003 Joint Conditional Probablity (Part 2) Priors.mp4 46MB
  111. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/007 Interacting with the Operating System and the Python Try-Catch Block.mp4 46MB
  112. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/027 Creating your First Word Cloud.mp4 46MB
  113. 05 - Predict House Prices with Multivariable Linear Regression/016 How to Shuffle and Split Training & Testing Data.mp4 45MB
  114. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/015 Saving a JSON File with Pandas.mp4 43MB
  115. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/016 Introduction to the Mean Squared Error (MSE).mp4 43MB
  116. 05 - Predict House Prices with Multivariable Linear Regression/005 Visualising Data (Part 1) Historams, Distributions & Outliers.mp4 43MB
  117. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/007 False Positive vs False Negatives.mp4 41MB
  118. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/033 Coding Challenge Find the Longest Email.mp4 41MB
  119. 05 - Predict House Prices with Multivariable Linear Regression/008 Understanding Descriptive Statistics the Mean vs the Median.mp4 41MB
  120. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/017 Data Visualisation (Part 2) Donut Charts.mp4 41MB
  121. 02 - Predict Movie Box Office Revenue with Linear Regression/002 Gather & Clean the Data.mp4 41MB
  122. 01 - Introduction to the Course/001 What is Machine Learning.mp4 40MB
  123. 05 - Predict House Prices with Multivariable Linear Regression/017 Running a Multivariable Regression.mp4 40MB
  124. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/011 Model Evaluation and the Confusion Matrix.mp4 40MB
  125. 01 - Introduction to the Course/002 What is Data Science.mp4 40MB
  126. 11 - Use Tensorflow to Classify Handwritten Digits/002 Getting the Data and Loading it into Numpy Arrays.mp4 40MB
  127. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/008 Reading Files (Part 1) Absolute Paths and Relative Paths.mp4 40MB
  128. 03 - Python Programming for Data Science and Machine Learning/002 Mac Users - Install Anaconda.mp4 39MB
  129. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/003 Introduction to Cost Functions.mp4 39MB
  130. 11 - Use Tensorflow to Classify Handwritten Digits/005 What is a Tensor.mp4 38MB
  131. 05 - Predict House Prices with Multivariable Linear Regression/006 Visualising Data (Part 2) Seaborn and Probability Density Functions.mp4 38MB
  132. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/018 Introduction to Natural Language Processing (NLP).mp4 37MB
  133. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/012 Create a Pandas DataFrame of Email Bodies.mp4 37MB
  134. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/004 Making Predictions Comparing Joint Probabilities.mp4 37MB
  135. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/022 Visualising the Optimisation on a 3D Surface.mp4 36MB
  136. 12 - Serving a Tensorflow Model through a Website/001 What you'll make.mp4 36MB
  137. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/005 Calculate the Token Probabilities and Save the Trained Model.mp4 35MB
  138. 03 - Python Programming for Data Science and Machine Learning/006 [Python] - Lists and Arrays.mp4 35MB
  139. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/009 The Precision Metric.mp4 34MB
  140. 12 - Serving a Tensorflow Model through a Website/017 Publish and Share your Website!.mp4 33MB
  141. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/001 The Human Brain and the Inspiration for Artificial Neural Networks.mp4 33MB
  142. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/015 Concatenating Numpy Arrays.mp4 32MB
  143. 03 - Python Programming for Data Science and Machine Learning/001 Windows Users - Install Anaconda.mp4 32MB
  144. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/002 Installing Tensorflow and Keras for Jupyter.mp4 32MB
  145. 05 - Predict House Prices with Multivariable Linear Regression/015 Understanding Multivariable Regression.mp4 32MB
  146. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/001 How to Translate a Business Problem into a Machine Learning Problem.mp4 31MB
  147. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/010 Extracting the Text in the Email Body.mp4 30MB
  148. 05 - Predict House Prices with Multivariable Linear Regression/001 Defining the Problem.mp4 30MB
  149. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier.mp4 29MB
  150. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/005 The Accuracy Metric.mp4 29MB
  151. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/006 Coding Challenge Prepare the Test Data.mp4 29MB
  152. 05 - Predict House Prices with Multivariable Linear Regression/024 How to Analyse and Plot Regression Residuals.mp4 28MB
  153. 03 - Python Programming for Data Science and Machine Learning/009 [Python] - Functions - Part 1 Defining and Calling Functions.mp4 27MB
  154. 02 - Predict Movie Box Office Revenue with Linear Regression/001 Introduction to Linear Regression & Specifying the Problem.mp4 27MB
  155. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/022 Creating a Function for Text Processing.mp4 26MB
  156. 12 - Serving a Tensorflow Model through a Website/011 Data Pre-Processing for Tensorflow.js.mp4 26MB
  157. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/004 Sum the Tokens across the Spam and Ham Subsets.mp4 24MB
  158. 12 - Serving a Tensorflow Model through a Website/008 Adding a Favicon.mp4 24MB
  159. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/18190700-SpamData.zip 23MB
  160. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/18190704-SpamData.zip 22MB
  161. 05 - Predict House Prices with Multivariable Linear Regression/018 How to Calculate the Model Fit with R-Squared.mp4 21MB
  162. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/18190724-SpamData.zip 21MB
  163. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/003 Gathering the CIFAR 10 Dataset.mp4 21MB
  164. 11 - Use Tensorflow to Classify Handwritten Digits/003 Data Exploration and Understanding the Structure of the Input Data.mp4 21MB
  165. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/001 Set up the Testing Notebook.mp4 20MB
  166. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/001 Solving a Business Problem with Image Classification.mp4 19MB
  167. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/003 How to Add the Lesson Resources to the Project.mp4 19MB
  168. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/037 Coding Challenge Solution Preparing the Test Data.mp4 19MB
  169. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/008 The Recall Metric.mp4 18MB
  170. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/010 The F-score or F1 Metric.mp4 16MB
  171. 03 - Python Programming for Data Science and Machine Learning/003 Does LSD Make You Better at Maths.mp4 16MB
  172. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/032 Coding Challenge Check for Membership in a Collection.mp4 15MB
  173. 11 - Use Tensorflow to Classify Handwritten Digits/18194656-MNIST.zip 15MB
  174. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/001 What's Coming Up.mp4 13MB
  175. 05 - Predict House Prices with Multivariable Linear Regression/009 Introduction to Correlation Understanding Strength & Direction.mp4 13MB
  176. 02 - Predict Movie Box Office Revenue with Linear Regression/004 The Intuition behind the Linear Regression Model.mp4 13MB
  177. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/002 How a Machine Learns.mp4 10MB
  178. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/005 Basic Probability.mp4 9MB
  179. 05 - Predict House Prices with Multivariable Linear Regression/019 Introduction to Model Evaluation.mp4 7MB
  180. 11 - Use Tensorflow to Classify Handwritten Digits/001 What's coming up.mp4 5MB
  181. 12 - Serving a Tensorflow Model through a Website/21028926-math-garden-stub-complete.zip 4MB
  182. 12 - Serving a Tensorflow Model through a Website/21028932-math-garden-stub-12.12-checkpoint.zip 4MB
  183. 05 - Predict House Prices with Multivariable Linear Regression/18179918-04-Multivariable-Regression.ipynb.zip 4MB
  184. 12 - Serving a Tensorflow Model through a Website/21028876-MNIST-Model-Load-Files.zip 3MB
  185. 03 - Python Programming for Data Science and Machine Learning/18204473-12-Rules-to-Learn-to-Code.pdf 2MB
  186. 12 - Serving a Tensorflow Model through a Website/21028894-TFJS.zip 2MB
  187. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/18179908-03-Gradient-Descent.ipynb.zip 1MB
  188. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/18179924-06-Bayes-Classifier-Pre-Processing.ipynb.zip 978KB
  189. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/18180490-09-Neural-Nets-Pretrained-Image-Classification.ipynb.zip 572KB
  190. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/18188466-TF-Keras-Classification-Images.zip 501KB
  191. 02 - Predict Movie Box Office Revenue with Linear Regression/9246634-cost-revenue-dirty.csv 375KB
  192. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/18180294-07-Bayes-Classifier-Testing-Inference-Evaluation.ipynb.zip 243KB
  193. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/18187728-10-Neural-Nets-Keras-CIFAR10-Classification.ipynb.zip 120KB
  194. 01 - Introduction to the Course/18162714-ML-Data-Science-Syllabus.pdf 104KB
  195. 02 - Predict Movie Box Office Revenue with Linear Regression/9249290-cost-revenue-clean.csv 91KB
  196. 02 - Predict Movie Box Office Revenue with Linear Regression/18175146-01-Linear-Regression-complete.ipynb.zip 75KB
  197. 12 - Serving a Tensorflow Model through a Website/21028914-math-garden-stub.zip 44KB
  198. 02 - Predict Movie Box Office Revenue with Linear Regression/18175084-01-Linear-Regression-checkpoint.ipynb.zip 38KB
  199. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/006 [Python] - Loops and the Gradient Descent Algorithm_en.vtt 38KB
  200. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/007 [Python] - Advanced Functions and the Pitfalls of Optimisation (Part 1)_en.vtt 37KB
  201. 03 - Python Programming for Data Science and Machine Learning/18179882-02-Python-Intro.ipynb.zip 36KB
  202. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/012 Model Evaluation and the Confusion Matrix_en.vtt 35KB
  203. 12 - Serving a Tensorflow Model through a Website/009 Styling an HTML Canvas_en.vtt 35KB
  204. 12 - Serving a Tensorflow Model through a Website/012 Introduction to OpenCV_en.vtt 34KB
  205. 12 - Serving a Tensorflow Model through a Website/006 HTML and CSS Styling_en.vtt 34KB
  206. 12 - Serving a Tensorflow Model through a Website/007 Loading a Tensorflow.js Model and Starting your own Server_en.vtt 34KB
  207. 12 - Serving a Tensorflow Model through a Website/016 Adding the Game Logic_en.vtt 34KB
  208. 12 - Serving a Tensorflow Model through a Website/010 Drawing on an HTML Canvas_en.vtt 33KB
  209. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/009 Understanding the Learning Rate_en.vtt 33KB
  210. 12 - Serving a Tensorflow Model through a Website/014 Calculating the Centre of Mass and Shifting the Image_en.vtt 32KB
  211. 03 - Python Programming for Data Science and Machine Learning/008 [Python] - Module Imports_en.vtt 31KB
  212. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/006 Visualising the Decision Boundary_en.vtt 30KB
  213. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/010 Use the Model to Make Predictions_en.vtt 30KB
  214. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/011 A Naive Bayes Implementation using SciKit Learn_en.vtt 29KB
  215. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/008 [Python] - Tuples and the Pitfalls of Optimisation (Part 2)_en.vtt 29KB
  216. 11 - Use Tensorflow to Classify Handwritten Digits/012 Different Model Architectures Experimenting with Dropout_en.vtt 27KB
  217. 02 - Predict Movie Box Office Revenue with Linear Regression/003 Explore & Visualise the Data with Python_en.vtt 27KB
  218. 11 - Use Tensorflow to Classify Handwritten Digits/006 Creating Tensors and Setting up the Neural Network Architecture_en.vtt 26KB
  219. 03 - Python Programming for Data Science and Machine Learning/012 [Python] - Objects - Understanding Attributes and Methods_en.vtt 26KB
  220. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/009 Use Regularisation to Prevent Overfitting Early Stopping & Dropout Techniques_en.vtt 25KB
  221. 05 - Predict House Prices with Multivariable Linear Regression/014 Working with Seaborn Pairplots & Jupyter Microbenchmarking Techniques_en.vtt 25KB
  222. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/002 Layers, Feature Generation and Learning_en.vtt 25KB
  223. 05 - Predict House Prices with Multivariable Linear Regression/031 Build a Valuation Tool (Part 3) Docstrings & Creating your own Python Module_en.vtt 25KB
  224. 03 - Python Programming for Data Science and Machine Learning/007 [Python & Pandas] - Dataframes and Series_en.vtt 24KB
  225. 12 - Serving a Tensorflow Model through a Website/013 Resizing and Adding Padding to Images_en.vtt 24KB
  226. 11 - Use Tensorflow to Classify Handwritten Digits/011 Name Scoping and Image Visualisation in Tensorboard_en.vtt 24KB
  227. 03 - Python Programming for Data Science and Machine Learning/014 Working with Python Objects to Analyse Data_en.vtt 24KB
  228. 12 - Serving a Tensorflow Model through a Website/003 Loading a SavedModel_en.vtt 23KB
  229. 03 - Python Programming for Data Science and Machine Learning/013 How to Make Sense of Python Documentation for Data Visualisation_en.vtt 23KB
  230. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/010 How to Create 3-Dimensional Charts_en.vtt 23KB
  231. 05 - Predict House Prices with Multivariable Linear Regression/022 Understanding VIF & Testing for Multicollinearity_en.vtt 22KB
  232. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/007 Interacting with the Operating System and the Python Try-Catch Block_en.vtt 22KB
  233. 11 - Use Tensorflow to Classify Handwritten Digits/009 Tensorboard Summaries and the Filewriter_en.vtt 21KB
  234. 05 - Predict House Prices with Multivariable Linear Regression/011 Visualising Correlations with a Heatmap_en.vtt 21KB
  235. 05 - Predict House Prices with Multivariable Linear Regression/027 Making Predictions (Part 1) MSE & R-Squared_en.vtt 21KB
  236. 05 - Predict House Prices with Multivariable Linear Regression/023 Model Simplification & Baysian Information Criterion_en.vtt 20KB
  237. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/014 Reshaping and Slicing N-Dimensional Arrays_en.vtt 20KB
  238. 05 - Predict House Prices with Multivariable Linear Regression/026 Residual Analysis (Part 2) Graphing and Comparing Regression Residuals_en.vtt 20KB
  239. 02 - Predict Movie Box Office Revenue with Linear Regression/005 Analyse and Evaluate the Results_en.vtt 20KB
  240. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/011 [Python] - Generator Functions & the yield Keyword_en.vtt 19KB
  241. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/035 Sparse Matrix (Part 2) Data Munging with Nested Loops_en.vtt 19KB
  242. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/021 Running Gradient Descent with a MSE Cost Function_en.vtt 19KB
  243. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/002 Create a Full Matrix_en.vtt 19KB
  244. 12 - Serving a Tensorflow Model through a Website/002 Saving Tensorflow Models_en.vtt 19KB
  245. 12 - Serving a Tensorflow Model through a Website/004 Converting a Model to Tensorflow.js_en.vtt 19KB
  246. 05 - Predict House Prices with Multivariable Linear Regression/020 Improving the Model by Transforming the Data_en.vtt 19KB
  247. 11 - Use Tensorflow to Classify Handwritten Digits/010 Understanding the Tensorflow Graph Nodes and Edges_en.vtt 19KB
  248. 05 - Predict House Prices with Multivariable Linear Regression/030 [Python] - Conditional Statements - Build a Valuation Tool (Part 2)_en.vtt 18KB
  249. 11 - Use Tensorflow to Classify Handwritten Digits/008 TensorFlow Sessions and Batching Data_en.vtt 18KB
  250. 03 - Python Programming for Data Science and Machine Learning/010 [Python] - Functions - Part 2 Arguments & Parameters_en.vtt 18KB
  251. 05 - Predict House Prices with Multivariable Linear Regression/012 Techniques to Style Scatter Plots_en.vtt 18KB
  252. 05 - Predict House Prices with Multivariable Linear Regression/007 Working with Index Data, Pandas Series, and Dummy Variables_en.vtt 18KB
  253. 05 - Predict House Prices with Multivariable Linear Regression/029 Build a Valuation Tool (Part 1) Working with Pandas Series & Numpy ndarrays_en.vtt 18KB
  254. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/005 Pre-processing Scaling Inputs and Creating a Validation Dataset_en.vtt 18KB
  255. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/011 Understanding Partial Derivatives and How to use SymPy_en.vtt 18KB
  256. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/006 Joint & Conditional Probability_en.vtt 17KB
  257. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/006 Making Predictions using InceptionResNet_en.vtt 17KB
  258. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/003 Costs and Disadvantages of Neural Networks_en.vtt 17KB
  259. 11 - Use Tensorflow to Classify Handwritten Digits/013 Prediction and Model Evaluation_en.vtt 17KB
  260. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/006 Compiling a Keras Model and Understanding the Cross Entropy Loss Function_en.vtt 17KB
  261. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/019 Tokenizing, Removing Stop Words and the Python Set Data Structure_en.vtt 17KB
  262. 05 - Predict House Prices with Multivariable Linear Regression/004 Clean and Explore the Data (Part 2) Find Missing Values_en.vtt 16KB
  263. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/003 Count the Tokens to Train the Naive Bayes Model_en.vtt 16KB
  264. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/004 Exploring the CIFAR Data_en.vtt 16KB
  265. 05 - Predict House Prices with Multivariable Linear Regression/025 Residual Analysis (Part 1) Predicted vs Actual Values_en.vtt 16KB
  266. 12 - Serving a Tensorflow Model through a Website/005 Introducing the Website Project and Tooling_en.vtt 16KB
  267. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/013 [Python] - Loops and Performance Considerations_en.vtt 16KB
  268. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/005 Understanding the Power Rule & Creating Charts with Subplots_en.vtt 16KB
  269. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/013 Cleaning Data (Part 1) Check for Empty Emails & Null Entries_en.vtt 16KB
  270. 05 - Predict House Prices with Multivariable Linear Regression/010 Calculating Correlations and the Problem posed by Multicollinearity_en.vtt 15KB
  271. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/031 Create the Vocabulary for the Spam Classifier_en.vtt 15KB
  272. 12 - Serving a Tensorflow Model through a Website/015 Making a Prediction from a Digit drawn on the HTML Canvas_en.vtt 15KB
  273. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/020 Plotting the Mean Squared Error (MSE) on a Surface (Part 2)_en.vtt 15KB
  274. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/004 LaTeX Markdown and Generating Data with Numpy_en.vtt 15KB
  275. 03 - Python Programming for Data Science and Machine Learning/015 [Python] - Tips, Code Style and Naming Conventions_en.vtt 15KB
  276. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/028 Styling the Word Cloud with a Mask_en.vtt 14KB
  277. 03 - Python Programming for Data Science and Machine Learning/005 [Python] - Variables and Types_en.vtt 14KB
  278. 03 - Python Programming for Data Science and Machine Learning/011 [Python] - Functions - Part 3 Results & Return Values_en.vtt 14KB
  279. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/004 Preprocessing Image Data and How RGB Works_en.vtt 14KB
  280. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/016 Data Visualisation (Part 1) Pie Charts_en.vtt 14KB
  281. 05 - Predict House Prices with Multivariable Linear Regression/003 Clean and Explore the Data (Part 1) Understand the Nature of the Dataset_en.vtt 14KB
  282. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/025 [Python] - Logical Operators to Create Subsets and Indices_en.vtt 13KB
  283. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/18180296-08-Naive-Bayes-with-scikit-learn.ipynb.zip 13KB
  284. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/007 Bayes Theorem_en.vtt 13KB
  285. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/034 Sparse Matrix (Part 1) Split the Training and Testing Data_en.vtt 13KB
  286. 05 - Predict House Prices with Multivariable Linear Regression/028 Making Predictions (Part 2) Standard Deviation, RMSE, and Prediction Intervals_en.vtt 13KB
  287. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/030 Styling Word Clouds with Custom Fonts_en.vtt 13KB
  288. 05 - Predict House Prices with Multivariable Linear Regression/024 How to Analyse and Plot Regression Residuals_en.vtt 13KB
  289. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/008 Fit a Keras Model and Use Tensorboard to Visualise Learning and Spot Problems_en.vtt 13KB
  290. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/009 Reading Files (Part 2) Stream Objects and Email Structure_en.vtt 13KB
  291. 11 - Use Tensorflow to Classify Handwritten Digits/007 Defining the Cross Entropy Loss Function, the Optimizer and the Metrics_en.vtt 13KB
  292. 05 - Predict House Prices with Multivariable Linear Regression/005 Visualising Data (Part 1) Historams, Distributions & Outliers_en.vtt 12KB
  293. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/002 Gathering Email Data and Working with Archives & Text Editors_en.vtt 12KB
  294. 02 - Predict Movie Box Office Revenue with Linear Regression/002 Gather & Clean the Data_en.vtt 12KB
  295. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/019 Understanding Nested Loops and Plotting the MSE Function (Part 1)_en.vtt 12KB
  296. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/027 Creating your First Word Cloud_en.vtt 12KB
  297. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/038 Checkpoint Understanding the Data_en.vtt 12KB
  298. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/007 Coding Challenge Solution Using other Keras Models_en.vtt 12KB
  299. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/024 Advanced Subsetting on DataFrames the apply() Function_en.vtt 12KB
  300. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/018 Implementing a MSE Cost Function_en.vtt 12KB
  301. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/017 Transposing and Reshaping Arrays_en.vtt 12KB
  302. 11 - Use Tensorflow to Classify Handwritten Digits/004 Data Preprocessing One-Hot Encoding and Creating the Validation Dataset_en.vtt 11KB
  303. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/007 False Positive vs False Negatives_en.vtt 11KB
  304. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/012 Implementing Batch Gradient Descent with SymPy_en.vtt 11KB
  305. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/002 Joint Conditional Probability (Part 1) Dot Product_en.vtt 11KB
  306. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/016 Introduction to the Mean Squared Error (MSE)_en.vtt 11KB
  307. 12 - Serving a Tensorflow Model through a Website/011 Data Pre-Processing for Tensorflow.js_en.vtt 11KB
  308. 05 - Predict House Prices with Multivariable Linear Regression/008 Understanding Descriptive Statistics the Mean vs the Median_en.vtt 11KB
  309. 03 - Python Programming for Data Science and Machine Learning/006 [Python] - Lists and Arrays_en.vtt 11KB
  310. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/026 Word Clouds & How to install Additional Python Packages_en.vtt 10KB
  311. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/036 Sparse Matrix (Part 3) Using groupby() and Saving .txt Files_en.vtt 10KB
  312. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/005 Importing Keras Models and the Tensorflow Graph_en.vtt 10KB
  313. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/008 Reading Files (Part 1) Absolute Paths and Relative Paths_en.vtt 10KB
  314. 05 - Predict House Prices with Multivariable Linear Regression/016 How to Shuffle and Split Training & Testing Data_en.vtt 10KB
  315. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/001 The Human Brain and the Inspiration for Artificial Neural Networks_en.vtt 10KB
  316. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/001 Setting up the Notebook and Understanding Delimiters in a Dataset_en.vtt 10KB
  317. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/021 Removing HTML tags with BeautifulSoup_en.vtt 10KB
  318. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/011 Model Evaluation and the Confusion Matrix_en.vtt 10KB
  319. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/003 Joint Conditional Probablity (Part 2) Priors_en.vtt 10KB
  320. 05 - Predict House Prices with Multivariable Linear Regression/021 How to Interpret Coefficients using p-Values and Statistical Significance_en.vtt 9KB
  321. 02 - Predict Movie Box Office Revenue with Linear Regression/004 The Intuition behind the Linear Regression Model_en.vtt 9KB
  322. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/020 Word Stemming & Removing Punctuation_en.vtt 9KB
  323. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/022 Visualising the Optimisation on a 3D Surface_en.vtt 9KB
  324. 03 - Python Programming for Data Science and Machine Learning/009 [Python] - Functions - Part 1 Defining and Calling Functions_en.vtt 9KB
  325. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/004 Making Predictions Comparing Joint Probabilities_en.vtt 9KB
  326. 12 - Serving a Tensorflow Model through a Website/001 What you'll make_en.vtt 9KB
  327. 05 - Predict House Prices with Multivariable Linear Regression/017 Running a Multivariable Regression_en.vtt 9KB
  328. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/001 How to Translate a Business Problem into a Machine Learning Problem_en.vtt 8KB
  329. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/009 The Precision Metric_en.vtt 8KB
  330. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/017 Data Visualisation (Part 2) Donut Charts_en.vtt 8KB
  331. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/005 Calculate the Token Probabilities and Save the Trained Model_en.vtt 8KB
  332. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/003 Introduction to Cost Functions_en.vtt 8KB
  333. 12 - Serving a Tensorflow Model through a Website/017 Publish and Share your Website!_en.vtt 8KB
  334. 11 - Use Tensorflow to Classify Handwritten Digits/002 Getting the Data and Loading it into Numpy Arrays_en.vtt 8KB
  335. 11 - Use Tensorflow to Classify Handwritten Digits/005 What is a Tensor_en.vtt 8KB
  336. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/014 Cleaning Data (Part 2) Working with a DataFrame Index_en.vtt 8KB
  337. 05 - Predict House Prices with Multivariable Linear Regression/006 Visualising Data (Part 2) Seaborn and Probability Density Functions_en.vtt 8KB
  338. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/015 Concatenating Numpy Arrays_en.vtt 8KB
  339. 03 - Python Programming for Data Science and Machine Learning/001 Windows Users - Install Anaconda_en.vtt 8KB
  340. 02 - Predict Movie Box Office Revenue with Linear Regression/001 Introduction to Linear Regression & Specifying the Problem_en.vtt 8KB
  341. 05 - Predict House Prices with Multivariable Linear Regression/002 Gathering the Boston House Price Data_en.vtt 8KB
  342. 05 - Predict House Prices with Multivariable Linear Regression/009 Introduction to Correlation Understanding Strength & Direction_en.vtt 7KB
  343. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/018 Introduction to Natural Language Processing (NLP)_en.vtt 7KB
  344. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/022 Creating a Function for Text Processing_en.vtt 7KB
  345. 03 - Python Programming for Data Science and Machine Learning/002 Mac Users - Install Anaconda_en.vtt 7KB
  346. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/004 Sum the Tokens across the Spam and Ham Subsets_en.vtt 7KB
  347. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/005 The Accuracy Metric_en.vtt 7KB
  348. 11 - Use Tensorflow to Classify Handwritten Digits/18187740-11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 7KB
  349. 05 - Predict House Prices with Multivariable Linear Regression/015 Understanding Multivariable Regression_en.vtt 7KB
  350. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/033 Coding Challenge Find the Longest Email_en.vtt 7KB
  351. 12 - Serving a Tensorflow Model through a Website/008 Adding a Favicon_en.vtt 6KB
  352. 03 - Python Programming for Data Science and Machine Learning/003 Does LSD Make You Better at Maths_en.vtt 6KB
  353. 12 - Serving a Tensorflow Model through a Website/21028850-11-Neural-Networks-TF-Handwriting-Recognition.ipynb.zip 6KB
  354. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/002 How a Machine Learns_en.vtt 6KB
  355. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/012 Create a Pandas DataFrame of Email Bodies_en.vtt 6KB
  356. 12 - Serving a Tensorflow Model through a Website/21028968-12-TF-SavedModel-Export-Completed.ipynb.zip 6KB
  357. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/015 Saving a JSON File with Pandas_en.vtt 6KB
  358. 01 - Introduction to the Course/001 What is Machine Learning_en.vtt 6KB
  359. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/002 Installing Tensorflow and Keras for Jupyter_en.vtt 6KB
  360. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/18180042-07-Bayes-Classifier-Training.ipynb.zip 6KB
  361. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/008 The Recall Metric_en.vtt 6KB
  362. 11 - Use Tensorflow to Classify Handwritten Digits/003 Data Exploration and Understanding the Structure of the Input Data_en.vtt 6KB
  363. 05 - Predict House Prices with Multivariable Linear Regression/001 Defining the Problem_en.vtt 6KB
  364. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/003 Gathering the CIFAR 10 Dataset_en.vtt 5KB
  365. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/004 The Naive Bayes Algorithm and the Decision Boundary for a Classifier_en.vtt 5KB
  366. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/032 Coding Challenge Check for Membership in a Collection_en.vtt 5KB
  367. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/029 Solving the Hamlet Challenge_en.vtt 5KB
  368. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/010 Extracting the Text in the Email Body_en.vtt 5KB
  369. 01 - Introduction to the Course/002 What is Data Science_en.vtt 5KB
  370. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/005 Basic Probability_en.vtt 5KB
  371. 12 - Serving a Tensorflow Model through a Website/21028978-x-test0-ylabel7.txt 5KB
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  374. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/006 Coding Challenge Prepare the Test Data_en.vtt 5KB
  375. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/001 Solving a Business Problem with Image Classification_en.vtt 4KB
  376. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/010 The F-score or F1 Metric_en.vtt 4KB
  377. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/003 How to Add the Lesson Resources to the Project_en.vtt 4KB
  378. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/037 Coding Challenge Solution Preparing the Test Data_en.vtt 4KB
  379. 13 - Next Steps/001 Where next.html 4KB
  380. 05 - Predict House Prices with Multivariable Linear Regression/018 How to Calculate the Model Fit with R-Squared_en.vtt 4KB
  381. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/001 What's Coming Up_en.vtt 3KB
  382. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/001 Set up the Testing Notebook_en.vtt 3KB
  383. 05 - Predict House Prices with Multivariable Linear Regression/019 Introduction to Model Evaluation_en.vtt 3KB
  384. 05 - Predict House Prices with Multivariable Linear Regression/18905386-boston-valuation.py 3KB
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  386. 11 - Use Tensorflow to Classify Handwritten Digits/001 What's coming up_en.vtt 2KB
  387. 01 - Introduction to the Course/004 Top Tips for Succeeding on this Course.html 2KB
  388. 03 - Python Programming for Data Science and Machine Learning/004 Download the 12 Rules to Learn to Code.html 1KB
  389. 01 - Introduction to the Course/005 Course Resources List.html 1KB
  390. 13 - Next Steps/003 Stay in Touch!.html 1KB
  391. 01 - Introduction to the Course/003 Download the Syllabus.html 994B
  392. 02 - Predict Movie Box Office Revenue with Linear Regression/007 Join the Student Community.html 715B
  393. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/008 Any Feedback on this Section.html 527B
  394. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/009 Any Feedback on this Section.html 526B
  395. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/014 Any Feedback on this Section.html 521B
  396. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/024 Any Feedback on this Section.html 520B
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  399. 02 - Predict Movie Box Office Revenue with Linear Regression/008 Any Feedback on this Section.html 512B
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  402. 12 - Serving a Tensorflow Model through a Website/018 Any Feedback on this Section.html 500B
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  404. 05 - Predict House Prices with Multivariable Linear Regression/013 A Note for the Next Lesson.html 476B
  405. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/023 A Note for the Next Lesson.html 476B
  406. 13 - Next Steps/002 What Modules Do You Want to See.html 431B
  407. 09 - Introduction to Neural Networks and How to Use Pre-Trained Models/008 Download the Complete Notebook Here.html 264B
  408. 02 - Predict Movie Box Office Revenue with Linear Regression/006 Download the Complete Notebook Here.html 242B
  409. 03 - Python Programming for Data Science and Machine Learning/016 Download the Complete Notebook Here.html 242B
  410. 04 - Introduction to Optimisation and the Gradient Descent Algorithm/023 Download the Complete Notebook Here.html 242B
  411. 05 - Predict House Prices with Multivariable Linear Regression/032 Download the Complete Notebook Here.html 242B
  412. 06 - Pre-Process Text Data for a Naive Bayes Classifier to Filter Spam Emails Part 1/039 Download the Complete Notebook Here.html 242B
  413. 07 - Train a Naive Bayes Classifier to Create a Spam Filter Part 2/007 Download the Complete Notebook Here.html 242B
  414. 08 - Test and Evaluate a Naive Bayes Classifier Part 3/012 Download the Complete Notebook Here.html 242B
  415. 10 - Build an Artificial Neural Network to Recognise Images using Keras & Tensorflow/013 Download the Complete Notebook Here.html 242B
  416. 11 - Use Tensorflow to Classify Handwritten Digits/014 Download the Complete Notebook Here.html 242B
  417. 02 - Predict Movie Box Office Revenue with Linear Regression/external-assets-links.txt 212B
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