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[FreeCourseSite.com] Udemy - PyTorch for Deep Learning in 2023 Zero to Mastery
magnet:?xt=urn:btih:aa903d0091c7b89352f43773cccd1d86586998e3&dn=[FreeCourseSite.com] Udemy - PyTorch for Deep Learning in 2023 Zero to Mastery
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aa903d0091c7b89352f43773cccd1d86586998e3
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23
文件大小:
29.69 GB
文件数量:
351
创建日期:
2023-12-31 02:32
最后访问:
2024-5-18 03:17
访问标签:
FreeCourseSite
com
Udemy
-
PyTorch
for
Deep
Learning
in
2023
Zero
to
Mastery
文件列表详情
1. Introduction/1. PyTorch for Deep Learning.mp4 75.35 MB
1. Introduction/2. Course Welcome and What Is Deep Learning.mp4 38.99 MB
1. Introduction/3. Join Our Online Classroom!.mp4 75.34 MB
1. Introduction/6. ZTM Resources.mp4 44.57 MB
10. PyTorch Paper Replicating/1. What Is a Machine Learning Research Paper.mp4 93.94 MB
10. PyTorch Paper Replicating/10. Breaking Down Figure 1 of the ViT Paper.mp4 87.11 MB
10. PyTorch Paper Replicating/11. Breaking Down the Four Equations Overview and a Trick for Reading Papers.mp4 140.92 MB
10. PyTorch Paper Replicating/12. Breaking Down Equation 1.mp4 103.21 MB
10. PyTorch Paper Replicating/13. Breaking Down Equation 2 and 3.mp4 125.03 MB
10. PyTorch Paper Replicating/14. Breaking Down Equation 4.mp4 92.43 MB
10. PyTorch Paper Replicating/15. Breaking Down Table 1.mp4 122.09 MB
10. PyTorch Paper Replicating/16. Calculating the Input and Output Shape of the Embedding Layer by Hand.mp4 160.59 MB
10. PyTorch Paper Replicating/17. Turning a Single Image into Patches (Part 1 Patching the Top Row).mp4 150.15 MB
10. PyTorch Paper Replicating/18. Turning a Single Image into Patches (Part 2 Patching the Entire Image).mp4 130.65 MB
10. PyTorch Paper Replicating/19. Creating Patch Embeddings with a Convolutional Layer.mp4 142.62 MB
10. PyTorch Paper Replicating/2. Why Replicate a Machine Learning Research Paper.mp4 23.26 MB
10. PyTorch Paper Replicating/20. Exploring the Outputs of Our Convolutional Patch Embedding Layer.mp4 129.06 MB
10. PyTorch Paper Replicating/21. Flattening Our Convolutional Feature Maps into a Sequence of Patch Embeddings.mp4 89.61 MB
10. PyTorch Paper Replicating/22. Visualizing a Single Sequence Vector of Patch Embeddings.mp4 50.37 MB
10. PyTorch Paper Replicating/23. Creating the Patch Embedding Layer with PyTorch.mp4 170.03 MB
10. PyTorch Paper Replicating/24. Creating the Class Token Embedding.mp4 131.98 MB
10. PyTorch Paper Replicating/25. Creating the Class Token Embedding - Less Birds.mp4 131.91 MB
10. PyTorch Paper Replicating/26. Creating the Position Embedding.mp4 109.18 MB
10. PyTorch Paper Replicating/27. Equation 1 Putting it All Together.mp4 134.81 MB
10. PyTorch Paper Replicating/28. Equation 2 Multihead Attention Overview.mp4 144.1 MB
10. PyTorch Paper Replicating/29. Equation 2 Layernorm Overview.mp4 111.75 MB
10. PyTorch Paper Replicating/3. Where Can You Find Machine Learning Research Papers and Code.mp4 110.76 MB
10. PyTorch Paper Replicating/30. Turning Equation 2 into Code.mp4 163.86 MB
10. PyTorch Paper Replicating/31. Checking the Inputs and Outputs of Equation.mp4 53.69 MB
10. PyTorch Paper Replicating/32. Equation 3 Replication Overview.mp4 88.7 MB
10. PyTorch Paper Replicating/33. Turning Equation 3 into Code.mp4 107.07 MB
10. PyTorch Paper Replicating/34. Transformer Encoder Overview.mp4 82.85 MB
10. PyTorch Paper Replicating/35. Combining equation 2 and 3 to Create the Transformer Encoder.mp4 84.87 MB
10. PyTorch Paper Replicating/36. Creating a Transformer Encoder Layer with In-Built PyTorch Layer.mp4 188.74 MB
10. PyTorch Paper Replicating/37. Bringing Our Own Vision Transformer to Life - Part 1 Gathering the Pieces.mp4 190.81 MB
10. PyTorch Paper Replicating/38. Bringing Our Own Vision Transformer to Life - Part 2 The Forward Method.mp4 111.37 MB
10. PyTorch Paper Replicating/39. Getting a Visual Summary of Our Custom Vision Transformer.mp4 84.89 MB
10. PyTorch Paper Replicating/4. What We Are Going to Cover.mp4 87.76 MB
10. PyTorch Paper Replicating/40. Creating a Loss Function and Optimizer from the ViT Paper.mp4 118.33 MB
10. PyTorch Paper Replicating/41. Training our Custom ViT on Food Vision Mini.mp4 53.47 MB
10. PyTorch Paper Replicating/42. Discussing what Our Training Setup Is Missing.mp4 101.19 MB
10. PyTorch Paper Replicating/43. Plotting a Loss Curve for Our ViT Model.mp4 63.39 MB
10. PyTorch Paper Replicating/44. Getting a Pretrained Vision Transformer from Torchvision and Setting it Up.mp4 164.75 MB
10. PyTorch Paper Replicating/45. Preparing Data to Be Used with a Pretrained ViT.mp4 57.21 MB
10. PyTorch Paper Replicating/46. Training a Pretrained ViT Feature Extractor Model for Food Vision Mini.mp4 76.28 MB
10. PyTorch Paper Replicating/47. Saving Our Pretrained ViT Model to File and Inspecting Its Size.mp4 40.36 MB
10. PyTorch Paper Replicating/48. Discussing the Trade-Offs Between Using a Larger Model for Deployments.mp4 41.81 MB
10. PyTorch Paper Replicating/49. Making Predictions on a Custom Image with Our Pretrained ViT.mp4 37.11 MB
10. PyTorch Paper Replicating/5. Getting Setup for Coding in Google Colab.mp4 99.13 MB
10. PyTorch Paper Replicating/50. PyTorch Paper Replicating Main Takeaways, Exercises and Extra-Curriculum.mp4 85.48 MB
10. PyTorch Paper Replicating/6. Downloading Data for Food Vision Mini.mp4 43.84 MB
10. PyTorch Paper Replicating/7. Turning Our Food Vision Mini Images into PyTorch DataLoaders.mp4 89.7 MB
10. PyTorch Paper Replicating/8. Visualizing a Single Image.mp4 36.44 MB
10. PyTorch Paper Replicating/9. Replicating a Vision Transformer - High Level Overview.mp4 77.83 MB
11. PyTorch Model Deployment/1. What is Machine Learning Model Deployment - Why Deploy a Machine Learning Model.mp4 73.83 MB
11. PyTorch Model Deployment/10. Creating an EffNetB2 Feature Extractor Model.mp4 92.12 MB
11. PyTorch Model Deployment/11. Create a Function to Make an EffNetB2 Feature Extractor Model and Transforms.mp4 57.59 MB
11. PyTorch Model Deployment/12. Creating DataLoaders for EffNetB2.mp4 31.38 MB
11. PyTorch Model Deployment/13. Training Our EffNetB2 Feature Extractor and Inspecting the Loss Curves.mp4 97.04 MB
11. PyTorch Model Deployment/14. Saving Our EffNetB2 Model to File.mp4 26.7 MB
11. PyTorch Model Deployment/15. Getting the Size of Our EffNetB2 Model in Megabytes.mp4 55.47 MB
11. PyTorch Model Deployment/16. Collecting Important Statistics and Performance Metrics for Our EffNetB2 Model.mp4 63.27 MB
11. PyTorch Model Deployment/17. Creating a Vision Transformer Feature Extractor Model.mp4 78.51 MB
11. PyTorch Model Deployment/18. Creating DataLoaders for Our ViT Feature Extractor Model.mp4 19.7 MB
11. PyTorch Model Deployment/19. Training Our ViT Feature Extractor Model and Inspecting Its Loss Curves.mp4 62 MB
11. PyTorch Model Deployment/2. Three Questions to Ask for Machine Learning Model Deployment.mp4 46.93 MB
11. PyTorch Model Deployment/20. Saving Our ViT Feature Extractor and Inspecting Its Size.mp4 43.77 MB
11. PyTorch Model Deployment/21. Collecting Stats About Our-ViT Feature Extractor.mp4 45.85 MB
11. PyTorch Model Deployment/22. Outlining the Steps for Making and Timing Predictions for Our Models.mp4 93.41 MB
11. PyTorch Model Deployment/23. Creating a Function to Make and Time Predictions with Our Models.mp4 185.77 MB
11. PyTorch Model Deployment/24. Making and Timing Predictions with EffNetB2.mp4 97.62 MB
11. PyTorch Model Deployment/25. Making and Timing Predictions with ViT.mp4 72.47 MB
11. PyTorch Model Deployment/26. Comparing EffNetB2 and ViT Model Statistics.mp4 89.62 MB
11. PyTorch Model Deployment/27. Visualizing the Performance vs Speed Trade-off.mp4 134.66 MB
11. PyTorch Model Deployment/28. Gradio Overview and Installation.mp4 95.13 MB
11. PyTorch Model Deployment/29. Gradio Function Outline.mp4 79.89 MB
11. PyTorch Model Deployment/3. Where Is My Model Going to Go.mp4 139.84 MB
11. PyTorch Model Deployment/30. Creating a Predict Function to Map Our Food Vision Mini Inputs to Outputs.mp4 95.22 MB
11. PyTorch Model Deployment/31. Creating a List of Examples to Pass to Our Gradio Demo.mp4 53.3 MB
11. PyTorch Model Deployment/32. Bringing Food Vision Mini to Life in a Live Web Application.mp4 135.38 MB
11. PyTorch Model Deployment/33. Getting Ready to Deploy Our App Hugging Face Spaces Overview.mp4 64.81 MB
11. PyTorch Model Deployment/34. Outlining the File Structure of Our Deployed App.mp4 89.53 MB
11. PyTorch Model Deployment/35. Creating a Food Vision Mini Demo Directory to House Our App Files.mp4 39.14 MB
11. PyTorch Model Deployment/36. Creating an Examples Directory with Example Food Vision Mini Images.mp4 92.4 MB
11. PyTorch Model Deployment/37. Writing Code to Move Our Saved EffNetB2 Model File.mp4 71.91 MB
11. PyTorch Model Deployment/38. Turning Our EffNetB2 Model Creation Function Into a Python Script.mp4 44.78 MB
11. PyTorch Model Deployment/39. Turning Our Food Vision Mini Demo App Into a Python Script.mp4 137.62 MB
11. PyTorch Model Deployment/4. How Is My Model Going to Function.mp4 67.36 MB
11. PyTorch Model Deployment/40. Creating a Requirements File for Our Food Vision Mini App.mp4 37.5 MB
11. PyTorch Model Deployment/41. Downloading Our Food Vision Mini App Files from Google Colab.mp4 112.22 MB
11. PyTorch Model Deployment/42. Uploading Our Food Vision Mini App to Hugging Face Spaces Programmatically.mp4 143.59 MB
11. PyTorch Model Deployment/43. Running Food Vision Mini on Hugging Face Spaces and Trying it Out.mp4 91.6 MB
11. PyTorch Model Deployment/44. Food Vision Big Project Outline.mp4 39.14 MB
11. PyTorch Model Deployment/45. Preparing an EffNetB2 Feature Extractor Model for Food Vision Big.mp4 96.52 MB
11. PyTorch Model Deployment/46. Downloading the Food 101 Dataset.mp4 71.66 MB
11. PyTorch Model Deployment/47. Creating a Function to Split Our Food 101 Dataset into Smaller Portions.mp4 119.73 MB
11. PyTorch Model Deployment/48. Turning Our Food 101 Datasets into DataLoaders.mp4 61.5 MB
11. PyTorch Model Deployment/49. Training Food Vision Big Our Biggest Model Yet!.mp4 184.21 MB
11. PyTorch Model Deployment/5. Some Tools and Places to Deploy Machine Learning Models.mp4 65.36 MB
11. PyTorch Model Deployment/50. Outlining the File Structure for Our Food Vision Big.mp4 52.77 MB
11. PyTorch Model Deployment/51. Downloading an Example Image and Moving Our Food Vision Big Model File.mp4 36.59 MB
11. PyTorch Model Deployment/52. Saving Food 101 Class Names to a Text File and Reading them Back In.mp4 66.82 MB
11. PyTorch Model Deployment/53. Turning Our EffNetB2 Feature Extractor Creation Function into a Python Script.mp4 23.9 MB
11. PyTorch Model Deployment/54. Creating an App Script for Our Food Vision Big Model Gradio Demo.mp4 104.81 MB
11. PyTorch Model Deployment/55. Zipping and Downloading Our Food Vision Big App Files.mp4 39.75 MB
11. PyTorch Model Deployment/56. Deploying Food Vision Big to Hugging Face Spaces.mp4 162.52 MB
11. PyTorch Model Deployment/57. PyTorch Mode Deployment Main Takeaways, Extra-Curriculum and Exercises.mp4 81.75 MB
11. PyTorch Model Deployment/6. What We Are Going to Cover.mp4 40.82 MB
11. PyTorch Model Deployment/7. Getting Setup to Code.mp4 62.89 MB
11. PyTorch Model Deployment/8. Downloading a Dataset for Food Vision Mini.mp4 39.25 MB
11. PyTorch Model Deployment/9. Outlining Our Food Vision Mini Deployment Goals and Modelling Experiments.mp4 58.55 MB
12. Introduction to PyTorch 2.0 and torch.compile/1. Introduction to PyTorch 2.0.mp4 82.16 MB
12. Introduction to PyTorch 2.0 and torch.compile/10. Creating a Function to Setup Our Model and Transforms.mp4 99.61 MB
12. Introduction to PyTorch 2.0 and torch.compile/11. Discussing How to Get Better Relative Speedups for Training Models.mp4 70.1 MB
12. Introduction to PyTorch 2.0 and torch.compile/12. Setting the Batch Size and Data Size Programmatically.mp4 70.98 MB
12. Introduction to PyTorch 2.0 and torch.compile/13. Getting More Potential Speedups with TensorFloat-32.mp4 83.85 MB
12. Introduction to PyTorch 2.0 and torch.compile/14. Downloading the CIFAR10 Dataset.mp4 67.55 MB
12. Introduction to PyTorch 2.0 and torch.compile/15. Creating Training and Test DataLoaders.mp4 67.81 MB
12. Introduction to PyTorch 2.0 and torch.compile/16. Preparing Training and Testing Loops with Timing Steps for PyTorch 2.0 timing.mp4 60.72 MB
12. Introduction to PyTorch 2.0 and torch.compile/17. Experiment 1 - Single Run without torch.compile.mp4 78.14 MB
12. Introduction to PyTorch 2.0 and torch.compile/18. Experiment 2 - Single Run with torch.compile.mp4 105.61 MB
12. Introduction to PyTorch 2.0 and torch.compile/19. Comparing the Results of Experiment 1 and 2.mp4 120.57 MB
12. Introduction to PyTorch 2.0 and torch.compile/2. What We Are Going to Cover and PyTorch 2 Reference Materials.mp4 15.08 MB
12. Introduction to PyTorch 2.0 and torch.compile/20. Saving the Results of Experiment 1 and 2.mp4 58.03 MB
12. Introduction to PyTorch 2.0 and torch.compile/21. Preparing Functions for Experiment 3 and 4.mp4 116.28 MB
12. Introduction to PyTorch 2.0 and torch.compile/22. Experiment 3 - Training a Non-Compiled Model for Multiple Runs.mp4 132.79 MB
12. Introduction to PyTorch 2.0 and torch.compile/23. Experiment 4 - Training a Compiled Model for Multiple Runs.mp4 104.98 MB
12. Introduction to PyTorch 2.0 and torch.compile/24. Comparing the Results of Experiment 3 and 4.mp4 62.82 MB
12. Introduction to PyTorch 2.0 and torch.compile/25. Potential Extensions and Resources to Learn More.mp4 64.06 MB
12. Introduction to PyTorch 2.0 and torch.compile/3. Getting Started with PyTorch 2 in Google Colab.mp4 44.58 MB
12. Introduction to PyTorch 2.0 and torch.compile/4. PyTorch 2.0 - 30 Second Intro.mp4 22.4 MB
12. Introduction to PyTorch 2.0 and torch.compile/5. Getting Setup for PyTorch 2.mp4 27.14 MB
12. Introduction to PyTorch 2.0 and torch.compile/6. Getting Info from Our GPUs and Seeing if They're Capable of Using PyTorch 2.mp4 77.55 MB
12. Introduction to PyTorch 2.0 and torch.compile/7. Setting the Default Device in PyTorch 2.mp4 102.96 MB
12. Introduction to PyTorch 2.0 and torch.compile/8. Discussing the Experiments We Are Going to Run for PyTorch 2.mp4 57.55 MB
12. Introduction to PyTorch 2.0 and torch.compile/9. Introduction to PyTorch 2.mp4 82.13 MB
14. Where To Go From Here/1. Thank You!.mp4 20.98 MB
2. PyTorch Fundamentals/1. Why Use Machine Learning or Deep Learning.mp4 13.81 MB
2. PyTorch Fundamentals/10. How To and How Not To Approach This Course.mp4 37.74 MB
2. PyTorch Fundamentals/11. Important Resources For This Course.mp4 58.32 MB
2. PyTorch Fundamentals/12. Getting Setup to Write PyTorch Code.mp4 69.99 MB
2. PyTorch Fundamentals/13. Introduction to PyTorch Tensors.mp4 93.99 MB
2. PyTorch Fundamentals/14. Creating Random Tensors in PyTorch.mp4 86.42 MB
2. PyTorch Fundamentals/15. Creating Tensors With Zeros and Ones in PyTorch.mp4 24.56 MB
2. PyTorch Fundamentals/16. Creating a Tensor Range and Tensors Like Other Tensors.mp4 32.59 MB
2. PyTorch Fundamentals/17. Dealing With Tensor Data Types.mp4 81.41 MB
2. PyTorch Fundamentals/18. Getting Tensor Attributes.mp4 66.44 MB
2. PyTorch Fundamentals/19. Manipulating Tensors (Tensor Operations).mp4 39.7 MB
2. PyTorch Fundamentals/2. The Number 1 Rule of Machine Learning and What Is Deep Learning Good For.mp4 35.33 MB
2. PyTorch Fundamentals/20. Matrix Multiplication (Part 1).mp4 77.8 MB
2. PyTorch Fundamentals/21. Matrix Multiplication (Part 2) The Two Main Rules of Matrix Multiplication.mp4 57.77 MB
2. PyTorch Fundamentals/22. Matrix Multiplication (Part 3) Dealing With Tensor Shape Errors.mp4 97.34 MB
2. PyTorch Fundamentals/23. Finding the Min Max Mean and Sum of Tensors (Tensor Aggregation).mp4 48.15 MB
2. PyTorch Fundamentals/24. Finding The Positional Min and Max of Tensors.mp4 24.49 MB
2. PyTorch Fundamentals/25. Reshaping, Viewing and Stacking Tensors.mp4 103.95 MB
2. PyTorch Fundamentals/26. Squeezing, Unsqueezing and Permuting Tensors.mp4 88.41 MB
2. PyTorch Fundamentals/27. Selecting Data From Tensors (Indexing).mp4 56.95 MB
2. PyTorch Fundamentals/28. PyTorch Tensors and NumPy.mp4 59.77 MB
2. PyTorch Fundamentals/29. PyTorch Reproducibility (Taking the Random Out of Random).mp4 95.11 MB
2. PyTorch Fundamentals/3. Machine Learning vs. Deep Learning.mp4 55.29 MB
2. PyTorch Fundamentals/30. Different Ways of Accessing a GPU in PyTorch.mp4 113.01 MB
2. PyTorch Fundamentals/31. Setting up Device-Agnostic Code and Putting Tensors On and Off the GPU.mp4 64.51 MB
2. PyTorch Fundamentals/32. PyTorch Fundamentals Exercises and Extra-Curriculum.mp4 56.76 MB
2. PyTorch Fundamentals/4. Anatomy of Neural Networks.mp4 70.32 MB
2. PyTorch Fundamentals/5. Different Types of Learning Paradigms.mp4 27.04 MB
2. PyTorch Fundamentals/6. What Can Deep Learning Be Used For.mp4 43.19 MB
2. PyTorch Fundamentals/7. What Is and Why PyTorch.mp4 113.55 MB
2. PyTorch Fundamentals/8. What Are Tensors.mp4 24.98 MB
2. PyTorch Fundamentals/9. What We Are Going To Cover With PyTorch.mp4 50.45 MB
3. PyTorch Workflow/1. Introduction and Where You Can Get Help.mp4 28.6 MB
3. PyTorch Workflow/10. Making Predictions With Our Random Model Using Inference Mode.mp4 107.03 MB
3. PyTorch Workflow/11. Training a Model Intuition (The Things We Need).mp4 69.49 MB
3. PyTorch Workflow/12. Setting Up an Optimizer and a Loss Function.mp4 116 MB
3. PyTorch Workflow/13. PyTorch Training Loop Steps and Intuition.mp4 128.78 MB
3. PyTorch Workflow/14. Writing Code for a PyTorch Training Loop.mp4 83 MB
3. PyTorch Workflow/15. Reviewing the Steps in a Training Loop Step by Step.mp4 177.45 MB
3. PyTorch Workflow/16. Running Our Training Loop Epoch by Epoch and Seeing What Happens.mp4 101.7 MB
3. PyTorch Workflow/17. Writing Testing Loop Code and Discussing What's Happening Step by Step.mp4 135.03 MB
3. PyTorch Workflow/18. Reviewing What Happens in a Testing Loop Step by Step.mp4 161.56 MB
3. PyTorch Workflow/19. Writing Code to Save a PyTorch Model.mp4 129.82 MB
3. PyTorch Workflow/2. Getting Setup and What We Are Covering.mp4 69.68 MB
3. PyTorch Workflow/20. Writing Code to Load a PyTorch Model.mp4 79.57 MB
3. PyTorch Workflow/21. Setting Up to Practice Everything We Have Done Using Device Agnostic code.mp4 45.79 MB
3. PyTorch Workflow/22. Putting Everything Together (Part 1) Data.mp4 49.34 MB
3. PyTorch Workflow/23. Putting Everything Together (Part 2) Building a Model.mp4 88.69 MB
3. PyTorch Workflow/24. Putting Everything Together (Part 3) Training a Model.mp4 102.99 MB
3. PyTorch Workflow/25. Putting Everything Together (Part 4) Making Predictions With a Trained Model.mp4 50.63 MB
3. PyTorch Workflow/26. Putting Everything Together (Part 5) Saving and Loading a Trained Model.mp4 72.53 MB
3. PyTorch Workflow/27. Exercise Imposter Syndrome.mp4 39.25 MB
3. PyTorch Workflow/28. PyTorch Workflow Exercises and Extra-Curriculum.mp4 49.31 MB
3. PyTorch Workflow/3. Creating a Simple Dataset Using the Linear Regression Formula.mp4 68.66 MB
3. PyTorch Workflow/4. Splitting Our Data Into Training and Test Sets.mp4 65.21 MB
3. PyTorch Workflow/5. Building a function to Visualize Our Data.mp4 61.89 MB
3. PyTorch Workflow/6. Creating Our First PyTorch Model for Linear Regression.mp4 130.08 MB
3. PyTorch Workflow/7. Breaking Down What's Happening in Our PyTorch Linear regression Model.mp4 62.18 MB
3. PyTorch Workflow/8. Discussing Some of the Most Important PyTorch Model Building Classes.mp4 74.44 MB
3. PyTorch Workflow/9. Checking Out the Internals of Our PyTorch Model.mp4 102.71 MB
4. PyTorch Neural Network Classification/1. Introduction to Machine Learning Classification With PyTorch.mp4 84.58 MB
4. PyTorch Neural Network Classification/10. Loss Function Optimizer and Evaluation Function for Our Classification Network.mp4 161.05 MB
4. PyTorch Neural Network Classification/11. Going from Model Logits to Prediction Probabilities to Prediction Labels.mp4 134.54 MB
4. PyTorch Neural Network Classification/12. Coding a Training and Testing Optimization Loop for Our Classification Model.mp4 126.75 MB
4. PyTorch Neural Network Classification/13. Writing Code to Download a Helper Function to Visualize Our Models Predictions.mp4 149.99 MB
4. PyTorch Neural Network Classification/14. Discussing Options to Improve a Model.mp4 80.86 MB
4. PyTorch Neural Network Classification/15. Creating a New Model with More Layers and Hidden Units.mp4 68.82 MB
4. PyTorch Neural Network Classification/16. Writing Training and Testing Code to See if Our Upgraded Model Performs Better.mp4 118.63 MB
4. PyTorch Neural Network Classification/17. Creating a Straight Line Dataset to See if Our Model is Learning Anything.mp4 61.35 MB
4. PyTorch Neural Network Classification/18. Building and Training a Model to Fit on Straight Line Data.mp4 71.67 MB
4. PyTorch Neural Network Classification/19. Evaluating Our Models Predictions on Straight Line Data.mp4 50.79 MB
4. PyTorch Neural Network Classification/2. Classification Problem Example Input and Output Shapes.mp4 49.96 MB
4. PyTorch Neural Network Classification/20. Introducing the Missing Piece for Our Classification Model Non-Linearity.mp4 96.52 MB
4. PyTorch Neural Network Classification/21. Building Our First Neural Network with Non-Linearity.mp4 92.59 MB
4. PyTorch Neural Network Classification/22. Writing Training and Testing Code for Our First Non-Linear Model.mp4 150.56 MB
4. PyTorch Neural Network Classification/23. Making Predictions with and Evaluating Our First Non-Linear Model.mp4 53.04 MB
4. PyTorch Neural Network Classification/24. Replicating Non-Linear Activation Functions with Pure PyTorch.mp4 80.74 MB
4. PyTorch Neural Network Classification/25. Putting It All Together (Part 1) Building a Multiclass Dataset.mp4 97.45 MB
4. PyTorch Neural Network Classification/26. Creating a Multi-Class Classification Model with PyTorch.mp4 107.43 MB
4. PyTorch Neural Network Classification/27. Setting Up a Loss Function and Optimizer for Our Multi-Class Model.mp4 65.06 MB
4. PyTorch Neural Network Classification/28. Logits to Prediction Probabilities to Prediction Labels with a Multi-Class Model.mp4 97.04 MB
4. PyTorch Neural Network Classification/29. Training a Multi-Class Classification Model and Troubleshooting Code on the Fly.mp4 150.08 MB
4. PyTorch Neural Network Classification/3. Typical Architecture of a Classification Neural Network (Overview).mp4 67.04 MB
4. PyTorch Neural Network Classification/30. Making Predictions with and Evaluating Our Multi-Class Classification Model.mp4 77.04 MB
4. PyTorch Neural Network Classification/31. Discussing a Few More Classification Metrics.mp4 97.54 MB
4. PyTorch Neural Network Classification/32. PyTorch Classification Exercises and Extra-Curriculum.mp4 41.46 MB
4. PyTorch Neural Network Classification/4. Making a Toy Classification Dataset.mp4 91.48 MB
4. PyTorch Neural Network Classification/5. Turning Our Data into Tensors and Making a Training and Test Split.mp4 81.06 MB
4. PyTorch Neural Network Classification/6. Laying Out Steps for Modelling and Setting Up Device-Agnostic Code.mp4 31.91 MB
4. PyTorch Neural Network Classification/7. Coding a Small Neural Network to Handle Our Classification Data.mp4 86.84 MB
4. PyTorch Neural Network Classification/8. Making Our Neural Network Visual.mp4 91.28 MB
4. PyTorch Neural Network Classification/9. Recreating and Exploring the Insides of Our Model Using nn.Sequential.mp4 123.24 MB
5. PyTorch Computer Vision/1. What Is a Computer Vision Problem and What We Are Going to Cover.mp4 113.66 MB
5. PyTorch Computer Vision/10. Creating a Loss Function an Optimizer for Model 0.mp4 110.53 MB
5. PyTorch Computer Vision/11. Creating a Function to Time Our Modelling Code.mp4 45.61 MB
5. PyTorch Computer Vision/12. Writing Training and Testing Loops for Our Batched Data.mp4 157.56 MB
5. PyTorch Computer Vision/13. Writing an Evaluation Function to Get Our Models Results.mp4 106.78 MB
5. PyTorch Computer Vision/14. Setup Device-Agnostic Code for Running Experiments on the GPU.mp4 44.32 MB
5. PyTorch Computer Vision/15. Model 1 Creating a Model with Non-Linear Functions.mp4 86.38 MB
5. PyTorch Computer Vision/16. Mode 1 Creating a Loss Function and Optimizer.mp4 31.33 MB
5. PyTorch Computer Vision/17. Turing Our Training Loop into a Function.mp4 70.88 MB
5. PyTorch Computer Vision/18. Turing Our Testing Loop into a Function.mp4 50.89 MB
5. PyTorch Computer Vision/19. Training and Testing Model 1 with Our Training and Testing Functions.mp4 108.43 MB
5. PyTorch Computer Vision/2. Computer Vision Input and Output Shapes.mp4 85.01 MB
5. PyTorch Computer Vision/20. Getting a Results Dictionary for Model 1.mp4 41.35 MB
5. PyTorch Computer Vision/21. Model 2 Convolutional Neural Networks High Level Overview.mp4 94.62 MB
5. PyTorch Computer Vision/22. Model 2 Coding Our First Convolutional Neural Network with PyTorch.mp4 208.33 MB
5. PyTorch Computer Vision/23. Model 2 Breaking Down Conv2D Step by Step.mp4 162.71 MB
5. PyTorch Computer Vision/24. Model 2 Breaking Down MaxPool2D Step by Step.mp4 158.1 MB
5. PyTorch Computer Vision/25. Mode 2 Using a Trick to Find the Input and Output Shapes of Each of Our Layers.mp4 174.82 MB
5. PyTorch Computer Vision/26. Model 2 Setting Up a Loss Function and Optimizer.mp4 27.87 MB
5. PyTorch Computer Vision/27. Model 2 Training Our First CNN and Evaluating Its Results.mp4 76.78 MB
5. PyTorch Computer Vision/28. Comparing the Results of Our Modelling Experiments.mp4 61.75 MB
5. PyTorch Computer Vision/29. Making Predictions on Random Test Samples with the Best Trained Model.mp4 83.66 MB
5. PyTorch Computer Vision/3. What Is a Convolutional Neural Network (CNN).mp4 55.4 MB
5. PyTorch Computer Vision/30. Plotting Our Best Model Predictions on Random Test Samples and Evaluating Them.mp4 63.48 MB
5. PyTorch Computer Vision/31. Making Predictions and Importing Libraries to Plot a Confusion Matrix.mp4 160.84 MB
5. PyTorch Computer Vision/32. Evaluating Our Best Models Predictions with a Confusion Matrix.mp4 67 MB
5. PyTorch Computer Vision/33. Saving and Loading Our Best Performing Model.mp4 98.15 MB
5. PyTorch Computer Vision/34. Recapping What We Have Covered Plus Exercises and Extra-Curriculum.mp4 81.89 MB
5. PyTorch Computer Vision/4. Discussing and Importing the Base Computer Vision Libraries in PyTorch.mp4 89.19 MB
5. PyTorch Computer Vision/5. Getting a Computer Vision Dataset and Checking Out Its- Input and Output Shapes.mp4 153.99 MB
5. PyTorch Computer Vision/6. Visualizing Random Samples of Data.mp4 68.11 MB
5. PyTorch Computer Vision/7. DataLoader Overview Understanding Mini-Batches.mp4 60.2 MB
5. PyTorch Computer Vision/8. Turning Our Datasets Into DataLoaders.mp4 100.23 MB
5. PyTorch Computer Vision/9. Model 0 Creating a Baseline Model with Two Linear Layers.mp4 136.88 MB
6. PyTorch Custom Datasets/1. What Is a Custom Dataset and What We Are Going to Cover.mp4 92.59 MB
6. PyTorch Custom Datasets/10. Visualizing a Loaded Image From the Train Dataset.mp4 76.72 MB
6. PyTorch Custom Datasets/11. Turning Our Image Datasets into PyTorch Dataloaders.mp4 84.32 MB
6. PyTorch Custom Datasets/12. Creating a Custom Dataset Class in PyTorch High Level Overview.mp4 74.7 MB
6. PyTorch Custom Datasets/13. Creating a Helper Function to Get Class Names From a Directory.mp4 79.09 MB
6. PyTorch Custom Datasets/14. Writing a PyTorch Custom Dataset Class from Scratch to Load Our Images.mp4 176.27 MB
6. PyTorch Custom Datasets/15. Compare Our Custom Dataset Class. to the Original Imagefolder Class.mp4 69.5 MB
6. PyTorch Custom Datasets/16. Writing a Helper Function to Visualize Random Images from Our Custom Dataset.mp4 131.21 MB
6. PyTorch Custom Datasets/17. Turning Our Custom Datasets Into DataLoaders.mp4 80.62 MB
6. PyTorch Custom Datasets/18. Exploring State of the Art Data Augmentation With Torchvision Transforms.mp4 166.35 MB
6. PyTorch Custom Datasets/19. Building a Baseline Model (Part 1) Loading and Transforming Data.mp4 77.93 MB
6. PyTorch Custom Datasets/2. Importing PyTorch and Setting Up Device Agnostic Code.mp4 48.96 MB
6. PyTorch Custom Datasets/20. Building a Baseline Model (Part 2) Replicating Tiny VGG from Scratch.mp4 117.22 MB
6. PyTorch Custom Datasets/21. Building a Baseline Model (Part 3)Doing a Forward Pass to Test Our Model Shapes.mp4 96.49 MB
6. PyTorch Custom Datasets/22. Using the Torchinfo Package to Get a Summary of Our Model.mp4 64.97 MB
6. PyTorch Custom Datasets/23. Creating Training and Testing loop Functions.mp4 106.16 MB
6. PyTorch Custom Datasets/24. Creating a Train Function to Train and Evaluate Our Models.mp4 103.47 MB
6. PyTorch Custom Datasets/25. Training and Evaluating Model 0 With Our Training Functions.mp4 89.27 MB
6. PyTorch Custom Datasets/26. Plotting the Loss Curves of Model 0.mp4 89.44 MB
6. PyTorch Custom Datasets/27. The Balance Between Overfitting and Underfitting and How to Deal With Each.mp4 131.81 MB
6. PyTorch Custom Datasets/28. Creating Augmented Training Datasets and DataLoaders for Model 1.mp4 98.83 MB
6. PyTorch Custom Datasets/29. Constructing and Training Model 1.mp4 60.64 MB
6. PyTorch Custom Datasets/3. Downloading a Custom Dataset of Pizza, Steak and Sushi Images.mp4 150.95 MB
6. PyTorch Custom Datasets/30. Plotting the Loss Curves of Model 1.mp4 31.69 MB
6. PyTorch Custom Datasets/31. Plotting the Loss Curves of All of Our Models Against Each Other.mp4 89.26 MB
6. PyTorch Custom Datasets/32. Predicting on Custom Data (Part 1) Downloading an Image.mp4 51.66 MB
6. PyTorch Custom Datasets/33. Predicting on Custom Data (Part 2) Loading In a Custom Image With PyTorch.mp4 68 MB
6. PyTorch Custom Datasets/34. Predicting on Custom Data (Part3)Getting Our Custom Image Into the Right Format.mp4 127.05 MB
6. PyTorch Custom Datasets/35. Predicting on Custom Data (Part4)Turning Our Models Raw Outputs Into Prediction.mp4 36.06 MB
6. PyTorch Custom Datasets/36. Predicting on Custom Data (Part 5) Putting It All Together.mp4 113.03 MB
6. PyTorch Custom Datasets/37. Summary of What We Have Covered Plus Exercises and Extra-Curriculum.mp4 73.32 MB
6. PyTorch Custom Datasets/4. Becoming One With the Data (Part 1) Exploring the Data Format.mp4 87.61 MB
6. PyTorch Custom Datasets/5. Becoming One With the Data (Part 2) Visualizing a Random Image.mp4 115.33 MB
6. PyTorch Custom Datasets/6. Becoming One With the Data (Part 3) Visualizing a Random Image with Matplotlib.mp4 51.91 MB
6. PyTorch Custom Datasets/7. Transforming Data (Part 1) Turning Images Into Tensors.mp4 81.71 MB
6. PyTorch Custom Datasets/8. Transforming Data (Part 2) Visualizing Transformed Images.mp4 127.58 MB
6. PyTorch Custom Datasets/9. Loading All of Our Images and Turning Them Into Tensors With ImageFolder.mp4 98.16 MB
7. PyTorch Going Modular/1. What Is Going Modular and What We Are Going to Cover.mp4 100.12 MB
7. PyTorch Going Modular/10. Going Modular Summary, Exercises and Extra-Curriculum.mp4 80.67 MB
7. PyTorch Going Modular/2. Going Modular Notebook (Part 1) Running It End to End.mp4 104.92 MB
7. PyTorch Going Modular/3. Downloading a Dataset.mp4 67.63 MB
7. PyTorch Going Modular/4. Writing the Outline for Our First Python Script to Setup the Data.mp4 156.79 MB
7. PyTorch Going Modular/5. Creating a Python Script to Create Our PyTorch DataLoaders.mp4 135.14 MB
7. PyTorch Going Modular/6. Turning Our Model Building Code into a Python Script.mp4 115.12 MB
7. PyTorch Going Modular/7. Turning Our Model Training Code into a Python Script.mp4 80 MB
7. PyTorch Going Modular/8. Turning Our Utility Function to Save a Model into a Python Script.mp4 75.79 MB
7. PyTorch Going Modular/9. Creating a Training Script to Train Our Model in One Line of Code.mp4 165.53 MB
8. PyTorch Transfer Learning/1. Introduction What is Transfer Learning and Why Use It.mp4 97.25 MB
8. PyTorch Transfer Learning/10. Different Kinds of Transfer Learning.mp4 56.96 MB
8. PyTorch Transfer Learning/11. Getting a Summary of the Different Layers of Our Model.mp4 76.03 MB
8. PyTorch Transfer Learning/12. Freezing the Base Layers of Our Model and Updating the Classifier Head.mp4 160.67 MB
8. PyTorch Transfer Learning/13. Training Our First Transfer Learning Feature Extractor Model.mp4 74.8 MB
8. PyTorch Transfer Learning/14. Plotting the Loss curves of Our Transfer Learning Model.mp4 58.93 MB
8. PyTorch Transfer Learning/15. Outlining the Steps to Make Predictions on the Test Images.mp4 66.74 MB
8. PyTorch Transfer Learning/16. Creating a Function Predict On and Plot Images.mp4 101.66 MB
8. PyTorch Transfer Learning/17. Making and Plotting Predictions on Test Images.mp4 78.14 MB
8. PyTorch Transfer Learning/18. Making a Prediction on a Custom Image.mp4 67.83 MB
8. PyTorch Transfer Learning/19. Main Takeaways, Exercises and Extra- Curriculum.mp4 44.43 MB
8. PyTorch Transfer Learning/2. Where Can You Find Pretrained Models and What We Are Going to Cover.mp4 55.86 MB
8. PyTorch Transfer Learning/3. Installing the Latest Versions of Torch and Torchvision.mp4 82.39 MB
8. PyTorch Transfer Learning/4. Downloading Our Previously Written Code from Going Modular.mp4 83.74 MB
8. PyTorch Transfer Learning/5. Downloading Pizza, Steak, Sushi Image Data from Github.mp4 72.16 MB
8. PyTorch Transfer Learning/6. Turning Our Data into DataLoaders with Manually Created Transforms.mp4 141.48 MB
8. PyTorch Transfer Learning/7. Turning Our Data into DataLoaders with Automatic Created Transforms.mp4 139.74 MB
8. PyTorch Transfer Learning/8. Which Pretrained Model Should You Use.mp4 128.78 MB
8. PyTorch Transfer Learning/9. Setting Up a Pretrained Model with Torchvision.mp4 113.14 MB
9. PyTorch Experiment Tracking/1. What Is Experiment Tracking and Why Track Experiments.mp4 61.85 MB
9. PyTorch Experiment Tracking/10. Creating a Function to Create SummaryWriter Instances.mp4 80.1 MB
9. PyTorch Experiment Tracking/11. Adapting Our Train Function to Be Able to Track Multiple Experiments.mp4 66.53 MB
9. PyTorch Experiment Tracking/12. What Experiments Should You Try.mp4 46.91 MB
9. PyTorch Experiment Tracking/13. Discussing the Experiments We Are Going to Try.mp4 48.29 MB
9. PyTorch Experiment Tracking/14. Downloading Datasets for Our Modelling Experiments.mp4 66.41 MB
9. PyTorch Experiment Tracking/15. Turning Our Datasets into DataLoaders Ready for Experimentation.mp4 78.06 MB
9. PyTorch Experiment Tracking/16. Creating Functions to Prepare Our Feature Extractor Models.mp4 159.2 MB
9. PyTorch Experiment Tracking/17. Coding Out the Steps to Run a Series of Modelling Experiments.mp4 127.61 MB
9. PyTorch Experiment Tracking/18. Running Eight Different Modelling Experiments in 5 Minutes.mp4 45.66 MB
9. PyTorch Experiment Tracking/19. Viewing Our Modelling Experiments in TensorBoard.mp4 140.29 MB
9. PyTorch Experiment Tracking/2. Getting Setup by Importing Torch Libraries and Going Modular Code.mp4 93.39 MB
9. PyTorch Experiment Tracking/20. Loading the Best Model and Making Predictions on Random Images from the Test Set.mp4 99.19 MB
9. PyTorch Experiment Tracking/21. Making a Prediction on Our Own Custom Image with the Best Model.mp4 39.71 MB
9. PyTorch Experiment Tracking/22. Main Takeaways, Exercises and Extra- Curriculum.mp4 43.6 MB
9. PyTorch Experiment Tracking/3. Creating a Function to Download Data.mp4 95.22 MB
9. PyTorch Experiment Tracking/4. Turning Our Data into DataLoaders Using Manual Transforms.mp4 92.72 MB
9. PyTorch Experiment Tracking/5. Turning Our Data into DataLoaders Using Automatic Transforms.mp4 82 MB
9. PyTorch Experiment Tracking/6. Preparing a Pretrained Model for Our Own Problem.mp4 113.16 MB
9. PyTorch Experiment Tracking/7. Setting Up a Way to Track a Single Model Experiment with TensorBoard.mp4 150.28 MB
9. PyTorch Experiment Tracking/8. Training a Single Model and Saving the Results to TensorBoard.mp4 41.79 MB
9. PyTorch Experiment Tracking/9. Exploring Our Single Models Results with TensorBoard.mp4 116.27 MB
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