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1. Creating a tensor.mp4
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MP4
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61.1 MB
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1. Creating a tensor.srt
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SRT
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9.6 KB
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1. Downloading a built-in dataset.mp4
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MP4
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39.5 MB
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1. Downloading a built-in dataset.srt
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SRT
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7.7 KB
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1. Downloading the dataset.mp4
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MP4
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49.8 MB
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1. Downloading the dataset.srt
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SRT
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7.2 KB
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1. General ensembling in machine learning.mp4
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MP4
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69.6 MB
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1. General ensembling in machine learning.srt
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SRT
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8.7 KB
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1. Installing packages in Google Colab.mp4
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MP4
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37.1 MB
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1. Installing packages in Google Colab.srt
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SRT
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5.2 KB
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1. Introduction.mp4
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MP4
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42 MB
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1. Introduction.srt
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SRT
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3.7 KB
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10. Saving and loading models.mp4
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MP4
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58.4 MB
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10. Saving and loading models.srt
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SRT
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10.6 KB
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10. Section conclusion.mp4
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MP4
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14.2 MB
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10. Section conclusion.srt
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SRT
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1.3 KB
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11. Problem statement and setup.mp4
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MP4
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20.1 MB
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11. Problem statement and setup.srt
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SRT
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4.9 KB
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12. Approaches and solutions.mp4
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MP4
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52.8 MB
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12. Approaches and solutions.srt
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SRT
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9.7 KB
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2. Ensembling in deep learning.mp4
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MP4
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65.9 MB
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2. Ensembling in deep learning.srt
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SRT
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10.3 KB
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2. Registering for a Google account.mp4
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MP4
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7.7 MB
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2. Registering for a Google account.srt
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SRT
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1.7 KB
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2. Tensor operations.mp4
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MP4
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40.5 MB
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2. Tensor operations.srt
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SRT
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8.2 KB
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2. Understanding the dataset.mp4
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MP4
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33 MB
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2. Understanding the dataset.srt
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SRT
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7.2 KB
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2. Working with PyTorch datasets.mp4
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MP4
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69.7 MB
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2. Working with PyTorch datasets.srt
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SRT
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9.2 KB
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2. Working with files using Google Drive.mp4
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MP4
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35.1 MB
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2. Working with files using Google Drive.srt
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SRT
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5.6 KB
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3. Convolutional network fundamentals.mp4
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MP4
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87.7 MB
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3. Convolutional network fundamentals.srt
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SRT
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11 KB
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3. Data versioning.mp4
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MP4
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45.4 MB
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3. Data versioning.srt
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SRT
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6.8 KB
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3. GPUs in the context of deep learning.mp4
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MP4
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70.6 MB
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3. GPUs in the context of deep learning.srt
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SRT
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6.8 KB
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3. Implementing a starting solution.mp4
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MP4
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60.4 MB
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3. Implementing a starting solution.srt
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SRT
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10.7 KB
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3. Loading a dataset into Colab.mp4
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MP4
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32.9 MB
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3. Loading a dataset into Colab.srt
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SRT
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6.2 KB
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3. Navigating to Google Colab.mp4
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MP4
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16.3 MB
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3. Navigating to Google Colab.srt
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SRT
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2.3 KB
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3. What is transfer learning.mp4
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MP4
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92.2 MB
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3. What is transfer learning.srt
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SRT
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11.2 KB
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3. Working with files directly in Google Colab.mp4
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MP4
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40.8 MB
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3. Working with files directly in Google Colab.srt
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SRT
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6.5 KB
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4. Building a PyTorch dataset.mp4
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MP4
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65.9 MB
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4. Building a PyTorch dataset.srt
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SRT
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11.6 KB
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4. Exploring your Google Colab Notebook.mp4
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MP4
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15.4 MB
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4. Exploring your Google Colab Notebook.srt
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SRT
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2.6 KB
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4. Implementation in PyTorch.mp4
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MP4
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48.8 MB
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4. Implementation in PyTorch.srt
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SRT
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9.6 KB
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4. Reproducibility.mp4
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MP4
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28.3 MB
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4. Reproducibility.srt
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SRT
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4.4 KB
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4. Sharing files via Google Drive.mp4
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MP4
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32.5 MB
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4. Sharing files via Google Drive.srt
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SRT
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5.7 KB
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4. The transfer learning workflow.mp4
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MP4
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68.2 MB
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4. The transfer learning workflow.srt
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SRT
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9.3 KB
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4. Training and evaluating.mp4
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MP4
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29.6 MB
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4. Training and evaluating.srt
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SRT
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6.6 KB
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4. Turning on your Colab GPU.mp4
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MP4
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19 MB
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4. Turning on your Colab GPU.srt
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SRT
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6 KB
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5. Choosing the size of input and output layers.mp4
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MP4
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53.8 MB
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5. Choosing the size of input and output layers.srt
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SRT
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6.5 KB
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5. Image augmentation fundamentals.mp4
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MP4
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69 MB
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5. Image augmentation fundamentals.srt
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SRT
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9.6 KB
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5. Introduction to version control with Git and GitHub.mp4
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MP4
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58.2 MB
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5. Introduction to version control with Git and GitHub.srt
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SRT
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5.9 KB
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5. Limits of the Colab GPU.mp4
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MP4
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29.9 MB
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5. Limits of the Colab GPU.srt
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SRT
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4.6 KB
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5. Residual network fundamentals.mp4
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MP4
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57.1 MB
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5. Residual network fundamentals.srt
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SRT
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7.6 KB
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5. The definition of notebooks.mp4
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MP4
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11.9 MB
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5. The definition of notebooks.srt
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SRT
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1.5 KB
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5. Training and evaluating.mp4
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MP4
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41 MB
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5. Training and evaluating.srt
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SRT
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8.9 KB
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5. When not to use deep learning.mp4
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MP4
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66.3 MB
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5. When not to use deep learning.srt
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SRT
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8.8 KB
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6. Choosing the size of hidden layers.mp4
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MP4
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87.9 MB
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6. Choosing the size of hidden layers.srt
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SRT
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12.6 KB
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6. Image augmentation in PyTorch.mp4
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MP4
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81.9 MB
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6. Image augmentation in PyTorch.srt
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SRT
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12.9 KB
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6. Neural network basics.mp4
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MP4
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37.4 MB
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6. Neural network basics.srt
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SRT
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4.8 KB
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6. Pretrained models for transfer learning.mp4
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MP4
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62.8 MB
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6. Pretrained models for transfer learning.srt
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SRT
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8.2 KB
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6. Residual blocks in convolutional networks.mp4
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MP4
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39.2 MB
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6. Residual blocks in convolutional networks.srt
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SRT
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6.6 KB
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6. Running your first Google Colab code cell.mp4
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MP4
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19.8 MB
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6. Running your first Google Colab code cell.srt
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SRT
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5.1 KB
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6. Sending Google Colab notebooks to GitHub.mp4
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MP4
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59.9 MB
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6. Sending Google Colab notebooks to GitHub.srt
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SRT
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9.4 KB
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7. Gradients and backpropagation.mp4
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MP4
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76.6 MB
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7. Gradients and backpropagation.srt
|
SRT
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10.3 KB
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7. Implementation in PyTorch.mp4
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MP4
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42.8 MB
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7. Implementation in PyTorch.srt
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SRT
|
7 KB
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7. Loss functions.mp4
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MP4
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68.9 MB
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7. Loss functions.srt
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SRT
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8.9 KB
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7. The markup language Markdown.mp4
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MP4
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15.8 MB
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7. The markup language Markdown.srt
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SRT
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2.4 KB
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8. Activation functions and weight initialization.mp4
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MP4
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76.6 MB
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8. Activation functions and weight initialization.srt
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SRT
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10.3 KB
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8. Automatic differentiation in PyTorch.mp4
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MP4
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43.1 MB
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8. Automatic differentiation in PyTorch.srt
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SRT
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9.5 KB
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8. Writing Markdown in Google Colab.mp4
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MP4
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12.5 MB
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8. Writing Markdown in Google Colab.srt
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SRT
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3.1 KB
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9. Optimizers.mp4
|
MP4
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90.2 MB
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9. Optimizers.srt
|
SRT
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10.7 KB
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9. Training a model.mp4
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MP4
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45.1 MB
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9. Training a model.srt
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SRT
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11.2 KB
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9. Writing LaTeX in Google Colab.mp4
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MP4
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17.6 MB
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9. Writing LaTeX in Google Colab.srt
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SRT
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1.8 KB
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Bonus Resources.txt
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TXT
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409.6 B
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|
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Get Bonus Downloads Here.url
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URL
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204.8 B
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