DevCourseWeb com Udemy Deep Learning with Google Colab | 6BC14DFEC0F4A484468DA8EDEDF20AFA90BA26A2

DevCourseWeb com Udemy Deep Learning with Google Colab

Name	[ DevCourseWeb.com ] Udemy - Deep Learning with Google Colab	DOWNLOAD Copy Link
Total Size	3.0 GB
Total Files	124
Last Seen	2024-10-06 23:53
Hash	6BC14DFEC0F4A484468DA8EDEDF20AFA90BA26A2

/
Get Bonus Downloads Here.url	0.2 KB
/.../1. Getting started in Google Colab/
1. Introduction.mp4	44.0 MB
1. Introduction.srt	3.8 KB
10. Section conclusion.mp4	14.8 MB
10. Section conclusion.srt	1.4 KB
2. Registering for a Google account.mp4	8.1 MB
2. Registering for a Google account.srt	1.8 KB
3. Navigating to Google Colab.mp4	17.1 MB
3. Navigating to Google Colab.srt	2.4 KB
4. Exploring your Google Colab Notebook.mp4	16.2 MB
4. Exploring your Google Colab Notebook.srt	2.6 KB
5. The definition of notebooks.mp4	12.4 MB
5. The definition of notebooks.srt	1.5 KB
6. Running your first Google Colab code cell.mp4	20.8 MB
6. Running your first Google Colab code cell.srt	5.2 KB
7. The markup language Markdown.mp4	16.5 MB
7. The markup language Markdown.srt	2.5 KB
8. Writing Markdown in Google Colab.mp4	13.1 MB
8. Writing Markdown in Google Colab.srt	3.1 KB
9. Writing LaTeX in Google Colab.mp4	18.4 MB
9. Writing LaTeX in Google Colab.srt	1.8 KB
/.../2. The ecosystem of Google Colab/
1. Installing packages in Google Colab.mp4	38.9 MB
1. Installing packages in Google Colab.srt	5.3 KB
2. Working with files using Google Drive.mp4	36.8 MB
2. Working with files using Google Drive.srt	5.8 KB
3. Working with files directly in Google Colab.mp4	42.7 MB
3. Working with files directly in Google Colab.srt	6.7 KB
4. Sharing files via Google Drive.mp4	34.1 MB
4. Sharing files via Google Drive.srt	5.8 KB
5. Introduction to version control with Git and GitHub.mp4	61.0 MB
5. Introduction to version control with Git and GitHub.srt	6.0 KB
6. Sending Google Colab notebooks to GitHub.mp4	62.8 MB
6. Sending Google Colab notebooks to GitHub.srt	9.6 KB
/.../3. Introduction to PyTorch/
1. Creating a tensor.mp4	64.1 MB
1. Creating a tensor.srt	9.8 KB
10. Saving and loading models.mp4	61.3 MB
10. Saving and loading models.srt	10.9 KB
11. Problem statement and setup.mp4	21.1 MB
11. Problem statement and setup.srt	5.0 KB
12. Approaches and solutions.mp4	55.3 MB
12. Approaches and solutions.srt	9.9 KB
2. Tensor operations.mp4	42.5 MB
2. Tensor operations.srt	8.4 KB
3. GPUs in the context of deep learning.mp4	74.1 MB
3. GPUs in the context of deep learning.srt	7.0 KB
4. Turning on your Colab GPU.mp4	19.9 MB
4. Turning on your Colab GPU.srt	6.1 KB
5. Limits of the Colab GPU.mp4	31.3 MB
5. Limits of the Colab GPU.srt	4.7 KB
6. Neural network basics.mp4	39.2 MB
6. Neural network basics.srt	4.9 KB
7. Gradients and backpropagation.mp4	80.3 MB
7. Gradients and backpropagation.srt	10.5 KB
8. Automatic differentiation in PyTorch.mp4	45.2 MB
8. Automatic differentiation in PyTorch.srt	9.7 KB
9. Training a model.mp4	47.3 MB
9. Training a model.srt	11.5 KB
/.../4. Working with datasets/
1. Downloading a built-in dataset.mp4	41.4 MB
1. Downloading a built-in dataset.srt	7.9 KB
2. Working with PyTorch datasets.mp4	73.1 MB
2. Working with PyTorch datasets.srt	9.4 KB
3. Loading a dataset into Colab.mp4	34.5 MB
3. Loading a dataset into Colab.srt	6.3 KB
4. Building a PyTorch dataset.mp4	69.1 MB
4. Building a PyTorch dataset.srt	11.9 KB
5. Image augmentation fundamentals.mp4	72.4 MB
5. Image augmentation fundamentals.srt	9.8 KB
6. Image augmentation in PyTorch.mp4	85.8 MB
6. Image augmentation in PyTorch.srt	13.2 KB
/.../5. Recognizing handwritten digits/
1. Downloading the dataset.mp4	33.9 MB
1. Downloading the dataset.srt	5.7 KB
2. Understanding the dataset.mp4	34.8 MB
2. Understanding the dataset.srt	7.7 KB
3. Implementing a starting solution.mp4	63.3 MB
3. Implementing a starting solution.srt	10.9 KB
4. Training and evaluating.mp4	31.1 MB
4. Training and evaluating.srt	6.7 KB
5. Choosing the size of input and output layers.mp4	56.4 MB
5. Choosing the size of input and output layers.srt	6.7 KB
6. Choosing the size of hidden layers.mp4	92.2 MB
6. Choosing the size of hidden layers.srt	12.9 KB
7. Loss functions.mp4	72.3 MB
7. Loss functions.srt	9.1 KB
8. Activation functions and weight initialization.mp4	80.4 MB
8. Activation functions and weight initialization.srt	10.6 KB
9. Optimizers.mp4	94.5 MB
9. Optimizers.srt	11.0 KB
/.../6. Transfer learning for object recognition/
1. Downloading the dataset.mp4	43.7 MB
1. Downloading the dataset.srt	8.9 KB
2. Understanding the dataset.mp4	53.9 MB
2. Understanding the dataset.srt	9.1 KB
3. What is transfer learning.mp4	96.7 MB
3. What is transfer learning.srt	11.4 KB
4. The transfer learning workflow.mp4	71.5 MB
4. The transfer learning workflow.srt	9.5 KB
5. Training and evaluating.mp4	43.0 MB
5. Training and evaluating.srt	9.1 KB
6. Pretrained models for transfer learning.mp4	65.9 MB
6. Pretrained models for transfer learning.srt	8.4 KB
/.../7. Recognizing fashion items/
1. Downloading the dataset.mp4	52.2 MB
1. Downloading the dataset.srt	7.4 KB
2. Understanding the dataset.mp4	34.6 MB
2. Understanding the dataset.srt	7.4 KB
3. Convolutional network fundamentals.mp4	92.0 MB
3. Convolutional network fundamentals.srt	11.3 KB
4. Implementation in PyTorch.mp4	51.2 MB
4. Implementation in PyTorch.srt	9.9 KB
5. Residual network fundamentals.mp4	59.9 MB
5. Residual network fundamentals.srt	7.7 KB
6. Residual blocks in convolutional networks.mp4	41.1 MB
6. Residual blocks in convolutional networks.srt	6.7 KB
7. Implementation in PyTorch.mp4	44.8 MB
7. Implementation in PyTorch.srt	7.2 KB
/.../8. Deep learning best practices/
1. General ensembling in machine learning.mp4	73.0 MB
1. General ensembling in machine learning.srt	8.9 KB
2. Ensembling in deep learning.mp4	69.1 MB
2. Ensembling in deep learning.srt	10.6 KB
3. Data versioning.mp4	47.7 MB
3. Data versioning.srt	6.9 KB
4. Reproducibility.mp4	29.7 MB
4. Reproducibility.srt	4.5 KB
5. When not to use deep learning.mp4	69.6 MB
5. When not to use deep learning.srt	9.0 KB
/~Get Your Files Here !/
Bonus Resources.txt	0.4 KB
Total files 124