Name                                                                                                             Size  
 Parent Directory                                                                                                   -   
 32. Training Your Deep Neural Network.mp4                                                                        167M  
 34. Make And Transform Predictions.mp4                                                                           155M  
 21. Turning Data Into Batches 2.mp4                                                                              149M  
 37. Visualizing And Evaluate Model Predictions 2.mp4                                                             144M  
 41. Making Predictions On Test Images.mp4                                                                        141M  
 40. Training Model On Full Dataset.mp4                                                                           140M  
 15. Preparing The Images.mp4                                                                                     134M  
 35. Transform Predictions To Text.mp4                                                                            130M  
 39. Saving And Loading A Trained Model.mp4                                                                       127M  
 22. Visualizing Our Data.mp4                                                                                     122M  
 25. Building A Deep Learning Model.mp4                                                                           122M  
 42. Submitting Model to Kaggle.mp4                                                                               121M  
 36. Visualizing Model Predictions.mp4                                                                            119M  
 43. Making Predictions On Our Images.mp4                                                                         119M  
 9. Importing TensorFlow 2.mp4                                                                                    117M  
 14. Loading Our Data Labels.mp4                                                                                  115M  
 38. Visualizing And Evaluate  Model Predictions 3.mp4                                                            113M  
 16. Turning Data Labels Into Numbers.mp4                                                                         107M  
 27. Building A Deep Learning Model 3.mp4                                                                         106M  
 26. Building A Deep Learning Model 2.mp4                                                                         106M  
 19. Preprocess Images 2.mp4                                                                                      105M  
 2. Deep Learning and Unstructured Data.mp4                                                                       102M  
 18. Preprocess Images.mp4                                                                                         90M  
 13. Optional Reloading Colab Notebook.mp4                                                                         89M  
 20. Turning Data Into Batches.mp4                                                                                 88M  
 28. Building A Deep Learning Model 4.mp4                                                                          86M  
 11. Using A GPU.mp4                                                                                               81M  
 30. Evaluating Our Model.mp4                                                                                      79M  
 4. Setting Up Google Colab.srt                                                                                    74M  
 4. Setting Up Google Colab.mp4                                                                                    74M  
 33. Evaluating Performance With TensorBoard.mp4                                                                   74M  
 17. Creating Our Own Validation Set.mp4                                                                           66M  
 6. Uploading Project Data.mp4                                                                                     52M  
 23. Preparing Our Inputs and Outputs.mp4                                                                          50M  
 12. Optional GPU and Google Colab.mp4                                                                             46M  
 29. Summarizing Our Model.mp4                                                                                     45M  
 7. Setting Up Our Data.mp4                                                                                        42M  
 5. Google Colab Workspace.mp4                                                                                     40M  
 31. Preventing Overfitting.mp4                                                                                    37M  
 10. Optional TensorFlow 2.0 Default Issue.srt                                                                     28M  
 10. Optional TensorFlow 2.0 Default Issue.mp4                                                                     28M  
 8. Setting Up Our Data 2.mp4                                                                                      21M  
 1. Section Overview.mp4                                                                                           12M  
 32. Training Your Deep Neural Network.srt                                                                         23K  
 41. Making Predictions On Test Images.srt                                                                         20K  
 2. Deep Learning and Unstructured Data.srt                                                                        20K  
 21. Turning Data Into Batches 2.srt                                                                               20K  
 34. Make And Transform Predictions.srt                                                                            19K  
 40. Training Model On Full Dataset.srt                                                                            19K  
 43. Making Predictions On Our Images.srt                                                                          19K  
 37. Visualizing And Evaluate Model Predictions 2.srt                                                              18K  
 35. Transform Predictions To Text.srt                                                                             18K  
 36. Visualizing Model Predictions.srt                                                                             17K  
 39. Saving And Loading A Trained Model.srt                                                                        17K  
 9. Importing TensorFlow 2.srt                                                                                     17K  
 42. Submitting Model to Kaggle.srt                                                                                17K  
 14. Loading Our Data Labels.srt                                                                                   16K  
 25. Building A Deep Learning Model.srt                                                                            16K  
 22. Visualizing Our Data.srt                                                                                      16K  
 15. Preparing The Images.srt                                                                                      15K  
 38. Visualizing And Evaluate  Model Predictions 3.srt                                                             14K  
 16. Turning Data Labels Into Numbers.srt                                                                          14K  
 18. Preprocess Images.srt                                                                                         13K  
 19. Preprocess Images 2.srt                                                                                       13K  
 26. Building A Deep Learning Model 2.srt                                                                          13K  
 11. Using A GPU.srt                                                                                               12K  
 28. Building A Deep Learning Model 4.srt                                                                          12K  
 20. Turning Data Into Batches.srt                                                                                 12K  
 17. Creating Our Own Validation Set.srt                                                                           11K  
 27. Building A Deep Learning Model 3.srt                                                                          11K  
 30. Evaluating Our Model.srt                                                                                      10K  
 33. Evaluating Performance With TensorBoard.srt                                                                  9.6K  
 6. Uploading Project Data.srt                                                                                    8.6K  
 23. Preparing Our Inputs and Outputs.srt                                                                         7.8K  
 13. Optional Reloading Colab Notebook.srt                                                                        7.8K  
 7. Setting Up Our Data.srt                                                                                       6.4K  
 5. Google Colab Workspace.srt                                                                                    6.3K  
 12. Optional GPU and Google Colab.srt                                                                            6.0K  
 29. Summarizing Our Model.srt                                                                                    6.0K  
 31. Preventing Overfitting.srt                                                                                   5.5K  
 44. Finishing Dog Vision Where to next.html                                                                      3.9K  
 1. Section Overview.srt                                                                                          2.8K  
 24. Optional How machines learn and what's going on behind the scenes.html                                       2.7K  
 8. Setting Up Our Data 2.srt                                                                                     2.2K  
 3. Setting Up With Google.html                                                                                   568   
 43.2 End-to-end Dog Vision Notebook (from the videos).html                                                       191   
 43.1 End-to-end Dog Vision Notebook (with annotations).html                                                      185   
 4.4 End-to-end Dog Vision Notebook (the project we'll be working through).html                                   182   
 42.1 Dog Vision Predictions with MobileNetV2 Ready for Kaggle Submission.html                                    180   
 27.1 Step by step breakdown of a convolutional neural network (what MobileNetV2 is made of).html                 172   
 41.1 Dog Vision Prediction Probabilities Array.html                                                              170   
 28.1 [Article] How to choose loss & activation functions when building a deep learning model.html                169   
 27.3 MobileNetV2 (the model we're using) architecture explanation by Sik-Ho Tsang.html                           163   
 31.1 Early Stopping Callback (a way to stop your model from training when it stops improving) Documentation.html 136   
 30.1 TensorBoard Callback Documentation.html                                                                     134   
 25.2 MobileNetV2 (the model we're using) on TensorFlow Hub.html                                                  132   
 14.1 Documentation on how many images Google recommends for image problems.html                                  129   
 10.1 Loading TensorFlow 2.0 into a Colab Notebook (if it isn't the default).html                                 129   
 35.1 TensorFlow documentation for the unbatch() function.html                                                    127   
 4.3 Kaggle Dog Breed Identification Competition (the basis of our upcoming project).html                         119   
 21.1 Yann LeCun's (OG of deep learning) Tweet on Batch Sizes.html                                                118   
 12.1 Introduction to Google Colab example notebook.html                                                          116   
 4.5 Introduction to Google Colab example notebook.html                                                           116   
 6.1 Kaggle Dog Breed Identification Competition Data.html                                                        115   
 18.1 Documentation for loading images in TensorFlow.html                                                         114   
 12.2 Google Colab Example of GPU speed up versus CPU.html                                                        114   
 11.1 Google Colab example GPU usage.html                                                                         114   
 6.2 Google Colab IO example (how to get data in and out of your Colab notebook).html                             113   
 4.2 Google Colab IO example (how to get data in and out of your Colab notebook).html                             113   
 5.1 Google Colab FAQ (things you should know about Google Colab).html                                            110   
 26.1 Keras in TensorFlow Overview Documentation.html                                                             108   
 17.1 Blog post by Rachel Thomas (of fast.ai) on how and why you should create a validation set.html              108   
 27.2 The Softmax Function (activation function we use in our model).html                                         107   
 18.2 TensorFlow guidelines for loading all kinds of data (turning your data into Tensors).html                    98   
 25.3 Andrei Karpathy's talk on AI at Tesla.html                                                                   95   
 5.2 Google Colab (our workspace for the upcoming project).html                                                    95   
 4.1 Google Colab (our workspace for the upcoming project).html                                                    95   
 25.4 Papers with Code (a great resource for some of the best machine learning papers with code examples).html     88   
 25.5 PyTorch Hub (PyTorch version of TensorFlow Hub).html                                                         85   
 25.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html                                 79   
 23.1 TensorFlow Hub (resource for pre-trained deep learning models and more).html                                 79   

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