Download PyTorch for Deep Learning in 2023: Zero to Mastery Torrent

Torrent Contents Size: 27.81 GB

PyTorch for Deep Learning in 2023: Zero to Mastery

1. Introduction

1. PyTorch for Deep Learning.mp4	MP4	75.35 MB
2. Course Welcome and What Is Deep Learning.mp4	MP4	38.99 MB
3. Join Our Online Classroom!.mp4	MP4	75.35 MB
4. Exercise Meet Your Classmates + Instructor.html	HTML	3.79 KB
5. Course Companion Book + Code + More.html	HTML	1.1 KB
6. Machine Learning + Python Monthly Newsletters.html	HTML	870 B

10. PyTorch Paper Replicating

1. What Is a Machine Learning Research Paper.mp4	MP4	93.94 MB
10. Breaking Down Figure 1 of the ViT Paper.mp4	MP4	87.12 MB
11. Breaking Down the Four Equations Overview and a Trick for Reading Papers.mp4	MP4	140.93 MB
12. Breaking Down Equation 1.mp4	MP4	103.22 MB
13. Breaking Down Equation 2 and 3.mp4	MP4	125.04 MB
14. Breaking Down Equation 4.mp4	MP4	92.44 MB
15. Breaking Down Table 1.mp4	MP4	122.08 MB
16. Calculating the Input and Output Shape of the Embedding Layer by Hand.mp4	MP4	160.6 MB
17. Turning a Single Image into Patches (Part 1 Patching the Top Row).mp4	MP4	150.16 MB
18. Turning a Single Image into Patches (Part 2 Patching the Entire Image).mp4	MP4	130.64 MB
19. Creating Patch Embeddings with a Convolutional Layer.mp4	MP4	142.63 MB
2. Why Replicate a Machine Learning Research Paper.mp4	MP4	23.26 MB
20. Exploring the Outputs of Our Convolutional Patch Embedding Layer.mp4	MP4	129.06 MB
21. Flattening Our Convolutional Feature Maps into a Sequence of Patch Embeddings.mp4	MP4	89.61 MB
22. Visualizing a Single Sequence Vector of Patch Embeddings.mp4	MP4	50.37 MB
23. Creating the Patch Embedding Layer with PyTorch.mp4	MP4	170.03 MB
24. Creating the Class Token Embedding.mp4	MP4	131.99 MB
25. Creating the Class Token Embedding - Less Birds.mp4	MP4	131.91 MB
26. Creating the Position Embedding.mp4	MP4	109.18 MB
27. Equation 1 Putting it All Together.mp4	MP4	134.82 MB
28. Equation 2 Multihead Attention Overview.mp4	MP4	144.11 MB
29. Equation 2 Layernorm Overview.mp4	MP4	111.76 MB
3. Where Can You Find Machine Learning Research Papers and Code.mp4	MP4	110.75 MB
30. Turning Equation 2 into Code.mp4	MP4	163.87 MB
31. Checking the Inputs and Outputs of Equation.mp4	MP4	53.69 MB
32. Equation 3 Replication Overview.mp4	MP4	88.7 MB
33. Turning Equation 3 into Code.mp4	MP4	107.07 MB
34. Transformer Encoder Overview.mp4	MP4	82.85 MB
35. Combining equation 2 and 3 to Create the Transformer Encoder.mp4	MP4	84.87 MB
36. Creating a Transformer Encoder Layer with In-Built PyTorch Layer.mp4	MP4	188.75 MB
37. Bringing Our Own Vision Transformer to Life - Part 1 Gathering the Pieces.mp4	MP4	190.82 MB
38. Bringing Our Own Vision Transformer to Life - Part 2 The Forward Method.mp4	MP4	111.37 MB
39. Getting a Visual Summary of Our Custom Vision Transformer.mp4	MP4	84.89 MB
4. What We Are Going to Cover.mp4	MP4	87.76 MB
40. Creating a Loss Function and Optimizer from the ViT Paper.mp4	MP4	118.33 MB
41. Training our Custom ViT on Food Vision Mini.mp4	MP4	53.48 MB
42. Discussing what Our Training Setup Is Missing.mp4	MP4	101.2 MB
43. Plotting a Loss Curve for Our ViT Model.mp4	MP4	63.4 MB
44. Getting a Pretrained Vision Transformer from Torchvision and Setting it Up.mp4	MP4	164.75 MB
45. Preparing Data to Be Used with a Pretrained ViT.mp4	MP4	57.22 MB
46. Training a Pretrained ViT Feature Extractor Model for Food Vision Mini.mp4	MP4	76.29 MB
47. Saving Our Pretrained ViT Model to File and Inspecting Its Size.mp4	MP4	40.36 MB
48. Discussing the Trade-Offs Between Using a Larger Model for Deployments.mp4	MP4	41.81 MB
49. Making Predictions on a Custom Image with Our Pretrained ViT.mp4	MP4	37.11 MB
5. Getting Setup for Coding in Google Colab.mp4	MP4	99.14 MB
50. PyTorch Paper Replicating Main Takeaways, Exercises and Extra-Curriculum.mp4	MP4	85.49 MB
6. Downloading Data for Food Vision Mini.mp4	MP4	43.83 MB
7. Turning Our Food Vision Mini Images into PyTorch DataLoaders.mp4	MP4	89.7 MB
8. Visualizing a Single Image.mp4	MP4	36.44 MB
9. Replicating a Vision Transformer - High Level Overview.mp4	MP4	77.84 MB

11. PyTorch Model Deployment

1. What is Machine Learning Model Deployment - Why Deploy a Machine Learning Model.mp4	MP4	73.84 MB
10. Creating an EffNetB2 Feature Extractor Model.mp4	MP4	92.12 MB
11. Create a Function to Make an EffNetB2 Feature Extractor Model and Transforms.mp4	MP4	57.6 MB
12. Creating DataLoaders for EffNetB2.mp4	MP4	31.38 MB
13. Training Our EffNetB2 Feature Extractor and Inspecting the Loss Curves.mp4	MP4	97.04 MB
14. Saving Our EffNetB2 Model to File.mp4	MP4	26.71 MB
15. Getting the Size of Our EffNetB2 Model in Megabytes.mp4	MP4	55.48 MB
16. Collecting Important Statistics and Performance Metrics for Our EffNetB2 Model.mp4	MP4	63.27 MB
17. Creating a Vision Transformer Feature Extractor Model.mp4	MP4	78.51 MB
18. Creating DataLoaders for Our ViT Feature Extractor Model.mp4	MP4	19.7 MB
19. Training Our ViT Feature Extractor Model and Inspecting Its Loss Curves.mp4	MP4	62 MB
2. Three Questions to Ask for Machine Learning Model Deployment.mp4	MP4	46.93 MB
20. Saving Our ViT Feature Extractor and Inspecting Its Size.mp4	MP4	43.77 MB
21. Collecting Stats About Our-ViT Feature Extractor.mp4	MP4	45.86 MB
22. Outlining the Steps for Making and Timing Predictions for Our Models.mp4	MP4	93.42 MB
23. Creating a Function to Make and Time Predictions with Our Models.mp4	MP4	185.78 MB
24. Making and Timing Predictions with EffNetB2.mp4	MP4	97.63 MB
25. Making and Timing Predictions with ViT.mp4	MP4	72.47 MB
26. Comparing EffNetB2 and ViT Model Statistics.mp4	MP4	89.62 MB
27. Visualizing the Performance vs Speed Trade-off.mp4	MP4	134.67 MB
28. Gradio Overview and Installation.mp4	MP4	95.13 MB
29. Gradio Function Outline.mp4	MP4	79.9 MB
3. Where Is My Model Going to Go.mp4	MP4	139.84 MB
30. Creating a Predict Function to Map Our Food Vision Mini Inputs to Outputs.mp4	MP4	95.22 MB
31. Creating a List of Examples to Pass to Our Gradio Demo.mp4	MP4	53.31 MB
32. Bringing Food Vision Mini to Life in a Live Web Application.mp4	MP4	135.39 MB
33. Getting Ready to Deploy Our App Hugging Face Spaces Overview.mp4	MP4	64.81 MB
34. Outlining the File Structure of Our Deployed App.mp4	MP4	89.54 MB
35. Creating a Food Vision Mini Demo Directory to House Our App Files.mp4	MP4	39.14 MB
36. Creating an Examples Directory with Example Food Vision Mini Images.mp4	MP4	92.41 MB
37. Writing Code to Move Our Saved EffNetB2 Model File.mp4	MP4	71.91 MB
38. Turning Our EffNetB2 Model Creation Function Into a Python Script.mp4	MP4	44.78 MB
39. Turning Our Food Vision Mini Demo App Into a Python Script.mp4	MP4	137.63 MB
4. How Is My Model Going to Function.mp4	MP4	67.36 MB
40. Creating a Requirements File for Our Food Vision Mini App.mp4	MP4	37.5 MB
41. Downloading Our Food Vision Mini App Files from Google Colab.mp4	MP4	112.22 MB
42. Uploading Our Food Vision Mini App to Hugging Face Spaces Programmatically.mp4	MP4	143.59 MB
43. Running Food Vision Mini on Hugging Face Spaces and Trying it Out.mp4	MP4	91.61 MB
44. Food Vision Big Project Outline.mp4	MP4	39.15 MB
45. Preparing an EffNetB2 Feature Extractor Model for Food Vision Big.mp4	MP4	96.53 MB
46. Downloading the Food 101 Dataset.mp4	MP4	71.67 MB
47. Creating a Function to Split Our Food 101 Dataset into Smaller Portions.mp4	MP4	119.74 MB
48. Turning Our Food 101 Datasets into DataLoaders.mp4	MP4	61.5 MB
49. Training Food Vision Big Our Biggest Model Yet!.mp4	MP4	184.22 MB
5. Some Tools and Places to Deploy Machine Learning Models.mp4	MP4	65.36 MB
50. Outlining the File Structure for Our Food Vision Big.mp4	MP4	52.78 MB
51. Downloading an Example Image and Moving Our Food Vision Big Model File.mp4	MP4	36.59 MB
52. Saving Food 101 Class Names to a Text File and Reading them Back In.mp4	MP4	66.81 MB
53. Turning Our EffNetB2 Feature Extractor Creation Function into a Python Script.mp4	MP4	23.9 MB
54. Creating an App Script for Our Food Vision Big Model Gradio Demo.mp4	MP4	104.81 MB
55. Zipping and Downloading Our Food Vision Big App Files.mp4	MP4	39.76 MB
56. Deploying Food Vision Big to Hugging Face Spaces.mp4	MP4	162.53 MB
57. PyTorch Mode Deployment Main Takeaways, Extra-Curriculum and Exercises.mp4	MP4	81.75 MB
6. What We Are Going to Cover.mp4	MP4	40.83 MB
7. Getting Setup to Code.mp4	MP4	62.88 MB
8. Downloading a Dataset for Food Vision Mini.mp4	MP4	39.25 MB
9. Outlining Our Food Vision Mini Deployment Goals and Modelling Experiments.mp4	MP4	58.56 MB
Download Paid Udemy Courses For Free.url	URL	116 B
GetFreeCourses.Co.url	URL	116 B

12. Where To Go From Here

1. Thank You!.mp4

MP4

20.99 MB

2. PyTorch Fundamentals

1. Why Use Machine Learning or Deep Learning.mp4	MP4	13.8 MB
10. How To and How Not To Approach This Course.mp4	MP4	37.74 MB
11. Important Resources For This Course.mp4	MP4	58.31 MB
12. Getting Setup to Write PyTorch Code.mp4	MP4	70 MB
13. Introduction to PyTorch Tensors.mp4	MP4	94 MB
14. Creating Random Tensors in PyTorch.mp4	MP4	86.42 MB
15. Creating Tensors With Zeros and Ones in PyTorch.mp4	MP4	24.56 MB
16. Creating a Tensor Range and Tensors Like Other Tensors.mp4	MP4	32.59 MB
17. Dealing With Tensor Data Types.mp4	MP4	81.4 MB
18. Getting Tensor Attributes.mp4	MP4	66.44 MB
19. Manipulating Tensors (Tensor Operations).mp4	MP4	39.7 MB
2. The Number 1 Rule of Machine Learning and What Is Deep Learning Good For.mp4	MP4	35.34 MB
20. Matrix Multiplication (Part 1).mp4	MP4	77.8 MB
21. Matrix Multiplication (Part 2) The Two Main Rules of Matrix Multiplication.mp4	MP4	57.78 MB
22. Matrix Multiplication (Part 3) Dealing With Tensor Shape Errors.mp4	MP4	97.35 MB
23. Finding the Min Max Mean and Sum of Tensors (Tensor Aggregation).mp4	MP4	48.14 MB
24. Finding The Positional Min and Max of Tensors.mp4	MP4	24.5 MB
25. Reshaping, Viewing and Stacking Tensors.mp4	MP4	103.95 MB
26. Squeezing, Unsqueezing and Permuting Tensors.mp4	MP4	88.41 MB
27. Selecting Data From Tensors (Indexing).mp4	MP4	56.96 MB
28. PyTorch Tensors and NumPy.mp4	MP4	59.78 MB
29. PyTorch Reproducibility (Taking the Random Out of Random).mp4	MP4	95.11 MB
3. Machine Learning vs. Deep Learning.mp4	MP4	55.3 MB
30. Different Ways of Accessing a GPU in PyTorch.mp4	MP4	113.01 MB
31. Setting up Device-Agnostic Code and Putting Tensors On and Off the GPU.mp4	MP4	64.51 MB
32. PyTorch Fundamentals Exercises and Extra-Curriculum.mp4	MP4	56.76 MB
33. Unlimited Updates.html	HTML	1.68 KB
4. Anatomy of Neural Networks.mp4	MP4	70.32 MB
5. Different Types of Learning Paradigms.mp4	MP4	27.05 MB
6. What Can Deep Learning Be Used For.mp4	MP4	43.2 MB
7. What Is and Why PyTorch.mp4	MP4	113.56 MB
8. What Are Tensors.mp4	MP4	24.99 MB
9. What We Are Going To Cover With PyTorch.mp4	MP4	50.45 MB
Download Paid Udemy Courses For Free.url	URL	116 B
GetFreeCourses.Co.url	URL	116 B

3. PyTorch Workflow

1. Introduction and Where You Can Get Help.mp4	MP4	28.6 MB
10. Making Predictions With Our Random Model Using Inference Mode.mp4	MP4	107.03 MB
11. Training a Model Intuition (The Things We Need).mp4	MP4	69.5 MB
12. Setting Up an Optimizer and a Loss Function.mp4	MP4	116 MB
13. PyTorch Training Loop Steps and Intuition.mp4	MP4	128.78 MB
14. Writing Code for a PyTorch Training Loop.mp4	MP4	83 MB
15. Reviewing the Steps in a Training Loop Step by Step.mp4	MP4	177.46 MB
16. Running Our Training Loop Epoch by Epoch and Seeing What Happens.mp4	MP4	101.7 MB
17. Writing Testing Loop Code and Discussing What's Happening Step by Step.mp4	MP4	135.03 MB
18. Reviewing What Happens in a Testing Loop Step by Step.mp4	MP4	161.56 MB
19. Writing Code to Save a PyTorch Model.mp4	MP4	129.82 MB
2. Getting Setup and What We Are Covering.mp4	MP4	69.67 MB
20. Writing Code to Load a PyTorch Model.mp4	MP4	79.58 MB
21. Setting Up to Practice Everything We Have Done Using Device Agnostic code.mp4	MP4	45.8 MB
22. Putting Everything Together (Part 1) Data.mp4	MP4	49.35 MB
23. Putting Everything Together (Part 2) Building a Model.mp4	MP4	88.7 MB
24. Putting Everything Together (Part 3) Training a Model.mp4	MP4	103 MB
25. Putting Everything Together (Part 4) Making Predictions With a Trained Model.mp4	MP4	50.63 MB
26. Putting Everything Together (Part 5) Saving and Loading a Trained Model.mp4	MP4	72.52 MB
27. Exercise Imposter Syndrome.mp4	MP4	39.25 MB
28. PyTorch Workflow Exercises and Extra-Curriculum.mp4	MP4	49.32 MB
3. Creating a Simple Dataset Using the Linear Regression Formula.mp4	MP4	68.65 MB
4. Splitting Our Data Into Training and Test Sets.mp4	MP4	65.22 MB
5. Building a function to Visualize Our Data.mp4	MP4	61.89 MB
6. Creating Our First PyTorch Model for Linear Regression.mp4	MP4	130.08 MB
7. Breaking Down What's Happening in Our PyTorch Linear regression Model.mp4	MP4	62.18 MB
8. Discussing Some of the Most Important PyTorch Model Building Classes.mp4	MP4	74.44 MB
9. Checking Out the Internals of Our PyTorch Model.mp4	MP4	102.71 MB

4. PyTorch Neural Network Classification

1. Introduction to Machine Learning Classification With PyTorch.mp4	MP4	84.58 MB
10. Loss Function Optimizer and Evaluation Function for Our Classification Network.mp4	MP4	161.06 MB
11. Going from Model Logits to Prediction Probabilities to Prediction Labels.mp4	MP4	134.54 MB
12. Coding a Training and Testing Optimization Loop for Our Classification Model.mp4	MP4	126.75 MB
13. Writing Code to Download a Helper Function to Visualize Our Models Predictions.mp4	MP4	149.99 MB
14. Discussing Options to Improve a Model.mp4	MP4	80.87 MB
15. Creating a New Model with More Layers and Hidden Units.mp4	MP4	68.81 MB
16. Writing Training and Testing Code to See if Our Upgraded Model Performs Better.mp4	MP4	118.64 MB
17. Creating a Straight Line Dataset to See if Our Model is Learning Anything.mp4	MP4	61.36 MB
18. Building and Training a Model to Fit on Straight Line Data.mp4	MP4	71.67 MB
19. Evaluating Our Models Predictions on Straight Line Data.mp4	MP4	50.8 MB
2. Classification Problem Example Input and Output Shapes.mp4	MP4	49.97 MB
20. Introducing the Missing Piece for Our Classification Model Non-Linearity.mp4	MP4	96.51 MB
21. Building Our First Neural Network with Non-Linearity.mp4	MP4	92.59 MB
22. Writing Training and Testing Code for Our First Non-Linear Model.mp4	MP4	150.57 MB
23. Making Predictions with and Evaluating Our First Non-Linear Model.mp4	MP4	53.05 MB
24. Replicating Non-Linear Activation Functions with Pure PyTorch.mp4	MP4	80.74 MB
25. Putting It All Together (Part 1) Building a Multiclass Dataset.mp4	MP4	97.46 MB
26. Creating a Multi-Class Classification Model with PyTorch.mp4	MP4	107.44 MB
27. Setting Up a Loss Function and Optimizer for Our Multi-Class Model.mp4	MP4	65.06 MB
28. Logits to Prediction Probabilities to Prediction Labels with a Multi-Class Model.mp4	MP4	97.05 MB
29. Training a Multi-Class Classification Model and Troubleshooting Code on the Fly.mp4	MP4	150.09 MB
3. Typical Architecture of a Classification Neural Network (Overview).mp4	MP4	67.05 MB
30. Making Predictions with and Evaluating Our Multi-Class Classification Model.mp4	MP4	77.05 MB
31. Discussing a Few More Classification Metrics.mp4	MP4	97.54 MB
32. PyTorch Classification Exercises and Extra-Curriculum.mp4	MP4	41.47 MB
4. Making a Toy Classification Dataset.mp4	MP4	91.48 MB
5. Turning Our Data into Tensors and Making a Training and Test Split.mp4	MP4	81.06 MB
6. Laying Out Steps for Modelling and Setting Up Device-Agnostic Code.mp4	MP4	31.92 MB
7. Coding a Small Neural Network to Handle Our Classification Data.mp4	MP4	86.85 MB
8. Making Our Neural Network Visual.mp4	MP4	91.27 MB
9. Recreating and Exploring the Insides of Our Model Using nn.Sequential.mp4	MP4	123.24 MB

5. PyTorch Computer Vision

1. What Is a Computer Vision Problem and What We Are Going to Cover.mp4	MP4	113.67 MB
10. Creating a Loss Function an Optimizer for Model 0.mp4	MP4	110.54 MB
11. Creating a Function to Time Our Modelling Code.mp4	MP4	45.61 MB
12. Writing Training and Testing Loops for Our Batched Data.mp4	MP4	157.56 MB
13. Writing an Evaluation Function to Get Our Models Results.mp4	MP4	106.79 MB
14. Setup Device-Agnostic Code for Running Experiments on the GPU.mp4	MP4	44.32 MB
15. Model 1 Creating a Model with Non-Linear Functions.mp4	MP4	86.39 MB
16. Mode 1 Creating a Loss Function and Optimizer.mp4	MP4	31.34 MB
17. Turing Our Training Loop into a Function.mp4	MP4	70.89 MB
18. Turing Our Testing Loop into a Function.mp4	MP4	50.89 MB
19. Training and Testing Model 1 with Our Training and Testing Functions.mp4	MP4	108.44 MB
2. Computer Vision Input and Output Shapes.mp4	MP4	85.02 MB
20. Getting a Results Dictionary for Model 1.mp4	MP4	41.35 MB
21. Model 2 Convolutional Neural Networks High Level Overview.mp4	MP4	94.63 MB
22. Model 2 Coding Our First Convolutional Neural Network with PyTorch.mp4	MP4	208.33 MB
23. Model 2 Breaking Down Conv2D Step by Step.mp4	MP4	162.72 MB
24. Model 2 Breaking Down MaxPool2D Step by Step.mp4	MP4	158.11 MB
25. Mode 2 Using a Trick to Find the Input and Output Shapes of Each of Our Layers.mp4	MP4	174.82 MB
26. Model 2 Setting Up a Loss Function and Optimizer.mp4	MP4	27.88 MB
27. Model 2 Training Our First CNN and Evaluating Its Results.mp4	MP4	76.79 MB
28. Comparing the Results of Our Modelling Experiments.mp4	MP4	61.76 MB
29. Making Predictions on Random Test Samples with the Best Trained Model.mp4	MP4	83.66 MB
3. What Is a Convolutional Neural Network (CNN).mp4	MP4	55.4 MB
30. Plotting Our Best Model Predictions on Random Test Samples and Evaluating Them.mp4	MP4	63.49 MB
31. Making Predictions and Importing Libraries to Plot a Confusion Matrix.mp4	MP4	160.84 MB
32. Evaluating Our Best Models Predictions with a Confusion Matrix.mp4	MP4	67.01 MB
33. Saving and Loading Our Best Performing Model.mp4	MP4	98.16 MB
34. Recapping What We Have Covered Plus Exercises and Extra-Curriculum.mp4	MP4	81.9 MB
4. Discussing and Importing the Base Computer Vision Libraries in PyTorch.mp4	MP4	89.2 MB
5. Getting a Computer Vision Dataset and Checking Out Its- Input and Output Shapes.mp4	MP4	154 MB
6. Visualizing Random Samples of Data.mp4	MP4	68.11 MB
7. DataLoader Overview Understanding Mini-Batches.mp4	MP4	60.21 MB
8. Turning Our Datasets Into DataLoaders.mp4	MP4	100.24 MB
9. Model 0 Creating a Baseline Model with Two Linear Layers.mp4	MP4	136.88 MB

6. PyTorch Custom Datasets

1. What Is a Custom Dataset and What We Are Going to Cover.mp4	MP4	92.59 MB
10. Visualizing a Loaded Image From the Train Dataset.mp4	MP4	76.73 MB
11. Turning Our Image Datasets into PyTorch Dataloaders.mp4	MP4	84.33 MB
12. Creating a Custom Dataset Class in PyTorch High Level Overview.mp4	MP4	74.7 MB
13. Creating a Helper Function to Get Class Names From a Directory.mp4	MP4	79.09 MB
14. Writing a PyTorch Custom Dataset Class from Scratch to Load Our Images.mp4	MP4	176.28 MB
15. Compare Our Custom Dataset Class. to the Original Imagefolder Class.mp4	MP4	69.5 MB
16. Writing a Helper Function to Visualize Random Images from Our Custom Dataset.mp4	MP4	131.22 MB
17. Turning Our Custom Datasets Into DataLoaders.mp4	MP4	80.62 MB
18. Exploring State of the Art Data Augmentation With Torchvision Transforms.mp4	MP4	166.35 MB
19. Building a Baseline Model (Part 1) Loading and Transforming Data.mp4	MP4	77.93 MB
2. Importing PyTorch and Setting Up Device Agnostic Code.mp4	MP4	48.97 MB
20. Building a Baseline Model (Part 2) Replicating Tiny VGG from Scratch.mp4	MP4	117.23 MB
21. Building a Baseline Model (Part 3)Doing a Forward Pass to Test Our Model Shapes.mp4	MP4	96.5 MB
22. Using the Torchinfo Package to Get a Summary of Our Model.mp4	MP4	64.97 MB
23. Creating Training and Testing loop Functions.mp4	MP4	106.17 MB
24. Creating a Train Function to Train and Evaluate Our Models.mp4	MP4	103.47 MB
25. Training and Evaluating Model 0 With Our Training Functions.mp4	MP4	89.28 MB
26. Plotting the Loss Curves of Model 0.mp4	MP4	89.45 MB
27. The Balance Between Overfitting and Underfitting and How to Deal With Each.mp4	MP4	131.82 MB
28. Creating Augmented Training Datasets and DataLoaders for Model 1.mp4	MP4	98.83 MB
29. Constructing and Training Model 1.mp4	MP4	60.65 MB
3. Downloading a Custom Dataset of Pizza, Steak and Sushi Images.mp4	MP4	150.96 MB
30. Plotting the Loss Curves of Model 1.mp4	MP4	31.69 MB
31. Plotting the Loss Curves of All of Our Models Against Each Other.mp4	MP4	89.27 MB
32. Predicting on Custom Data (Part 1) Downloading an Image.mp4	MP4	51.66 MB
33. Predicting on Custom Data (Part 2) Loading In a Custom Image With PyTorch.mp4	MP4	67.99 MB
34. Predicting on Custom Data (Part3)Getting Our Custom Image Into the Right Format.mp4	MP4	127.06 MB
35. Predicting on Custom Data (Part4)Turning Our Models Raw Outputs Into Prediction.mp4	MP4	36.07 MB
36. Predicting on Custom Data (Part 5) Putting It All Together.mp4	MP4	113.03 MB
37. Summary of What We Have Covered Plus Exercises and Extra-Curriculum.mp4	MP4	73.32 MB
4. Becoming One With the Data (Part 1) Exploring the Data Format.mp4	MP4	87.61 MB
5. Becoming One With the Data (Part 2) Visualizing a Random Image.mp4	MP4	115.34 MB
6. Becoming One With the Data (Part 3) Visualizing a Random Image with Matplotlib.mp4	MP4	51.91 MB
7. Transforming Data (Part 1) Turning Images Into Tensors.mp4	MP4	81.72 MB
8. Transforming Data (Part 2) Visualizing Transformed Images.mp4	MP4	127.58 MB
9. Loading All of Our Images and Turning Them Into Tensors With ImageFolder.mp4	MP4	98.17 MB
Download Paid Udemy Courses For Free.url	URL	116 B
GetFreeCourses.Co.url	URL	116 B

7. PyTorch Going Modular

1. What Is Going Modular and What We Are Going to Cover.mp4	MP4	100.12 MB
10. Going Modular Summary, Exercises and Extra-Curriculum.mp4	MP4	80.67 MB
2. Going Modular Notebook (Part 1) Running It End to End.mp4	MP4	104.92 MB
3. Downloading a Dataset.mp4	MP4	67.64 MB
4. Writing the Outline for Our First Python Script to Setup the Data.mp4	MP4	156.79 MB
5. Creating a Python Script to Create Our PyTorch DataLoaders.mp4	MP4	135.14 MB
6. Turning Our Model Building Code into a Python Script.mp4	MP4	115.13 MB
7. Turning Our Model Training Code into a Python Script.mp4	MP4	80 MB
8. Turning Our Utility Function to Save a Model into a Python Script.mp4	MP4	75.79 MB
9. Creating a Training Script to Train Our Model in One Line of Code.mp4	MP4	165.52 MB

8. PyTorch Transfer Learning

1. Introduction What is Transfer Learning and Why Use It.mp4	MP4	97.26 MB
10. Different Kinds of Transfer Learning.mp4	MP4	56.96 MB
11. Getting a Summary of the Different Layers of Our Model.mp4	MP4	76.04 MB
12. Freezing the Base Layers of Our Model and Updating the Classifier Head.mp4	MP4	160.67 MB
13. Training Our First Transfer Learning Feature Extractor Model.mp4	MP4	74.81 MB
14. Plotting the Loss curves of Our Transfer Learning Model.mp4	MP4	58.93 MB
15. Outlining the Steps to Make Predictions on the Test Images.mp4	MP4	66.74 MB
16. Creating a Function Predict On and Plot Images.mp4	MP4	101.67 MB
17. Making and Plotting Predictions on Test Images.mp4	MP4	78.14 MB
18. Making a Prediction on a Custom Image.mp4	MP4	67.83 MB
19. Main Takeaways, Exercises and Extra- Curriculum.mp4	MP4	44.43 MB
2. Where Can You Find Pretrained Models and What We Are Going to Cover.mp4	MP4	55.85 MB
3. Installing the Latest Versions of Torch and Torchvision.mp4	MP4	82.39 MB
4. Downloading Our Previously Written Code from Going Modular.mp4	MP4	83.75 MB
5. Downloading Pizza, Steak, Sushi Image Data from Github.mp4	MP4	72.17 MB
6. Turning Our Data into DataLoaders with Manually Created Transforms.mp4	MP4	141.48 MB
7. Turning Our Data into DataLoaders with Automatic Created Transforms.mp4	MP4	139.74 MB
8. Which Pretrained Model Should You Use.mp4	MP4	128.78 MB
9. Setting Up a Pretrained Model with Torchvision.mp4	MP4	113.15 MB

9. PyTorch Experiment Tracking

1. What Is Experiment Tracking and Why Track Experiments.mp4	MP4	61.86 MB
10. Creating a Function to Create SummaryWriter Instances.mp4	MP4	80.1 MB
11. Adapting Our Train Function to Be Able to Track Multiple Experiments.mp4	MP4	66.54 MB
12. What Experiments Should You Try.mp4	MP4	46.92 MB
13. Discussing the Experiments We Are Going to Try.mp4	MP4	48.3 MB
14. Downloading Datasets for Our Modelling Experiments.mp4	MP4	66.42 MB
15. Turning Our Datasets into DataLoaders Ready for Experimentation.mp4	MP4	78.07 MB
16. Creating Functions to Prepare Our Feature Extractor Models.mp4	MP4	159.21 MB
17. Coding Out the Steps to Run a Series of Modelling Experiments.mp4	MP4	127.62 MB
18. Running Eight Different Modelling Experiments in 5 Minutes.mp4	MP4	45.66 MB
19. Viewing Our Modelling Experiments in TensorBoard.mp4	MP4	140.3 MB
2. Getting Setup by Importing Torch Libraries and Going Modular Code.mp4	MP4	93.39 MB
20. Loading the Best Model and Making Predictions on Random Images from the Test Set.mp4	MP4	99.19 MB
21. Making a Prediction on Our Own Custom Image with the Best Model.mp4	MP4	39.71 MB
22. Main Takeaways, Exercises and Extra- Curriculum.mp4	MP4	43.59 MB
3. Creating a Function to Download Data.mp4	MP4	95.23 MB
4. Turning Our Data into DataLoaders Using Manual Transforms.mp4	MP4	92.72 MB
5. Turning Our Data into DataLoaders Using Automatic Transforms.mp4	MP4	82.01 MB
6. Preparing a Pretrained Model for Our Own Problem.mp4	MP4	113.16 MB
7. Setting Up a Way to Track a Single Model Experiment with TensorBoard.mp4	MP4	150.28 MB
8. Training a Single Model and Saving the Results to TensorBoard.mp4	MP4	41.79 MB
9. Exploring Our Single Models Results with TensorBoard.mp4	MP4	116.26 MB

Download Paid Udemy Courses For Free.url

URL

116 B

GetFreeCourses.Co.url

URL

116 B

Description

									Show full description
								

Related Torrents

TORRENT NAME	SIZE	FILES	AGE	SEED	LEECH	SOURCE
Udemy - PyTorch for Deep Learning in 2023: Zero to Mastery Posted by fcs0310 in Other Posted in Other 7 29.7 GB 2 years ago fcs0310	Size 29.7 GB	Files 1	Age 2 years ago	Seeds 7	Leechs 3	Source
ZeroToMastery] - PyTorch for Deep Learning (Giga Course) Posted by CourseClub in Other Posted in Other 2 14.8 GB 3 years ago CourseClub	Size 14.8 GB	Files 2	Age 3 years ago	Seeds 2	Leechs 0	Source
ZeroToMastery - PyTorch for Deep Learning (Course Club) Posted by CourseClub in Other Posted in Other 2 16 GB 3 years ago CourseClub	Size 16 GB	Files 329	Age 3 years ago	Seeds 2	Leechs 0	Source
ZeroToMastery \| PyTorch for Deep Learning [FCO] Posted by SunRiseZone in Other Posted in Other 19 16 GB 3 years ago SunRiseZone	Size 16 GB	Files 329	Age 3 years ago	Seeds 19	Leechs 4	Source
Deep Learning with PyTorch for Medical Image Analysis Posted by cybil18 in Other Posted in Other 5 3.64 GB 4 years ago cybil18	Size 3.64 GB	Files 92	Age 4 years ago	Seeds 5	Leechs 2	Source

PyTorch for Deep Learning in 2023: Zero to Mastery

Torrent Contents Size: 27.81 GB

Description

Related Torrents

Location

Trackers

Latest News

Latest Searches

Sites In Our Index

Popular Tags

Tracker name
udp://tracker.coppersurfer.tk:6969/announce
udp://9.rarbg.me:2850/announce
udp://9.rarbg.to:2920/announce
udp://tracker.opentrackr.org:1337
udp://tracker.leechers-paradise.org:6969/announce