Deep Learning Computer VisionTM CNN OpenCV YOLO SSD GANs Udemy Course
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Deep Learning Computer VisionTM CNN OpenCV YOLO SSD GANs Udemy Course
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Deep Learning Computer VisionTM CNN OpenCV YOLO SSD GANs Udemy Course
[CourseClub.ME].url -
[FCS Forum].url -
[FreeCourseSite.com].url -
1. Course Introduction.mp4 -
1. Course Introduction.srt -
1. Data Augmentation Chapter Overview.mp4 -
1. Data Augmentation Chapter Overview.srt -
2. Splitting Data into Test and Training Datasets.mp4 -
2. Splitting Data into Test and Training Datasets.srt -
2.1 datasets.zip.zip -
3. Train a Cats vs. Dogs Classifier.mp4 -
3. Train a Cats vs. Dogs Classifier.srt -
4. Boosting Accuracy with Data Augmentation.mp4 -
4. Boosting Accuracy with Data Augmentation.srt -
5. Types of Data Augmentation.mp4 -
5. Types of Data Augmentation.srt -
1. Introduction to the Confusion Matrix & Viewing Misclassifications.mp4 -
1. Introduction to the Confusion Matrix & Viewing Misclassifications.srt -
2. Understanding the Confusion Matrix.mp4 -
2. Understanding the Confusion Matrix.srt -
3. Finding and Viewing Misclassified Data.mp4 -
3. Finding and Viewing Misclassified Data.srt -
1. Introduction to the types of Optimizers, Learning Rates & Callbacks.mp4 -
1. Introduction to the types of Optimizers, Learning Rates & Callbacks.srt -
2. Types Optimizers and Adaptive Learning Rate Methods.mp4 -
2. Types Optimizers and Adaptive Learning Rate Methods.srt -
3. Keras Callbacks and Checkpoint, Early Stopping and Adjust Learning Rates that Pl.mp4 -
3. Keras Callbacks and Checkpoint, Early Stopping and Adjust Learning Rates that Pl.srt -
4. Build a Fruit Classifier.mp4 -
4. Build a Fruit Classifier.srt -
4.1 fruits-360.tar.gz.gz -
1. Intro to Building LeNet, AlexNet in Keras & Understand Batch Normalization.mp4 -
1. Intro to Building LeNet, AlexNet in Keras & Understand Batch Normalization.srt -
2. Build LeNet and test on MNIST.mp4 -
2. Build LeNet and test on MNIST.srt -
3. Build AlexNet and test on CIFAR10.mp4 -
3. Build AlexNet and test on CIFAR10.srt -
4. Batch Normalization.mp4 -
4. Batch Normalization.srt -
5. Build a Clothing & Apparel Classifier (Fashion MNIST).mp4 -
5. Build a Clothing & Apparel Classifier (Fashion MNIST).srt -
5.1 fashion_mnist.tar.gz.gz -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. ImageNet - Experimenting with pre-trained Models in Keras (VGG16, ResNet50, Mobi.mp4 -
2. ImageNet - Experimenting with pre-trained Models in Keras (VGG16, ResNet50, Mobi.srt -
3. Understanding VGG16 and VGG19.mp4 -
3. Understanding VGG16 and VGG19.srt -
4. Understanding ResNet50.mp4 -
4. Understanding ResNet50.srt -
5. Understanding InceptionV3.mp4 -
5. Understanding InceptionV3.srt -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. What is Transfer Learning and Fine Tuning.mp4 -
2. What is Transfer Learning and Fine Tuning.srt -
3. Build a Monkey Breed Classifier with MobileNet using Transfer Learning.mp4 -
3. Build a Monkey Breed Classifier with MobileNet using Transfer Learning.srt -
3.1 17_flowers.tar.gz.gz -
4. Build a Flower Classifier with VGG16 using Transfer Learning.mp4 -
4. Build a Flower Classifier with VGG16 using Transfer Learning.srt -
4.1 monkey_breed.zip.zip -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. Introducing LittleVGG.mp4 -
2. Introducing LittleVGG.srt -
3. Simpsons Character Recognition using LittleVGG.mp4 -
3. Simpsons Character Recognition using LittleVGG.srt -
3.1 simpsons.tar.gz.gz -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. Dying ReLU Problem and Introduction to Leaky ReLU, ELU and PReLUs.mp4 -
2. Dying ReLU Problem and Introduction to Leaky ReLU, ELU and PReLUs.srt -
3. Advanced Initializations.mp4 -
3. Advanced Initializations.srt -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. Build an Emotion, Facial Expression Detector.mp4 -
2. Build an Emotion, Facial Expression Detector.srt -
2.1 fer2013.zip.zip -
3. Build EmotionAgeGender Recognition in our Deep Surveillance Monitor.mp4 -
3. Build EmotionAgeGender Recognition in our Deep Surveillance Monitor.srt -
3.1 age-gender-estimation.tar.gz.gz -
1. Chapter Overview on Image Segmentation & Medical Imaging in U-Net.mp4 -
1. Chapter Overview on Image Segmentation & Medical Imaging in U-Net.srt -
2. What is Segmentation And Applications in Medical Imaging.mp4 -
2. What is Segmentation And Applications in Medical Imaging.srt -
3. U-Net Image Segmentation with CNNs.mp4 -
3. U-Net Image Segmentation with CNNs.srt -
4. The Intersection over Union (IoU) Metric.mp4 -
4. The Intersection over Union (IoU) Metric.srt -
5. Finding the Nuclei in Divergent Images.mp4 -
5. Finding the Nuclei in Divergent Images.srt -
5.1 U_NET.zip.zip -
1. Introduction to Computer Vision & Deep Learning.mp4 -
1. Introduction to Computer Vision & Deep Learning.srt -
2. What is Computer Vision and What Makes it Hard.mp4 -
2. What is Computer Vision and What Makes it Hard.srt -
3. What are Images.mp4 -
3. What are Images.srt -
4. Intro to OpenCV, OpenVINO™ & their Limitations.mp4 -
4. Intro to OpenCV, OpenVINO™ & their Limitations.srt -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. Object Detection Introduction - Sliding Windows with HOGs.mp4 -
2. Object Detection Introduction - Sliding Windows with HOGs.srt -
3. R-CNN, Fast R-CNN, Faster R-CNN and Mask R-CNN.mp4 -
3. R-CNN, Fast R-CNN, Faster R-CNN and Mask R-CNN.srt -
4. Single Shot Detectors (SSDs).mp4 -
4. Single Shot Detectors (SSDs).srt -
5. YOLO to YOLOv3.mp4 -
5. YOLO to YOLOv3.srt -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. TFOD API Install and Setup.mp4 -
2. TFOD API Install and Setup.srt -
2.1 Download the code (for those not using the Virtual Machine).html -
3. Experiment with a ResNet SSD on images, webcam and videos.mp4 -
3. Experiment with a ResNet SSD on images, webcam and videos.srt -
4. How to Train a TFOD Model.mp4 -
4. How to Train a TFOD Model.srt -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. Setting up and install Yolo DarkNet and DarkFlow.mp4 -
2. Setting up and install Yolo DarkNet and DarkFlow.srt -
2.1 Guide to the MacOS Install.html -
2.2 Download the YOLO files (if not using the VM).html -
3. Experiment with YOLO on still images, webcam and videos.mp4 -
3. Experiment with YOLO on still images, webcam and videos.srt -
4. Build your own YOLO Object Detector - Detecting London Underground Signs.mp4 -
4. Build your own YOLO Object Detector - Detecting London Underground Signs.srt -
4.1 LondonUnderground_train.tar.gz.gz -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. DeepDream – How AI Generated Art All Started.mp4 -
2. DeepDream – How AI Generated Art All Started.srt -
3. Neural Style Transfer.mp4 -
3. Neural Style Transfer.srt -
1. Generative Adverserial Neural Networks Chapter Overview.mp4 -
1. Generative Adverserial Neural Networks Chapter Overview.srt -
2. Introduction To GANs.mp4 -
2. Introduction To GANs.srt -
3. Mathematics of GANs.mp4 -
3. Mathematics of GANs.srt -
4. Implementing GANs in Keras.mp4 -
4. Implementing GANs in Keras.srt -
5. Face Aging GAN.mp4 -
5. Face Aging GAN.srt -
5.1 GenerativeNetworks.tar.gz.gz -
1. Basic Face Recognition using LittleVGG CNN.html -
1.1 25. Face Recognition All Notebooks.tar.gz.gz -
2. Face Matching with VGGFace.html -
2.1 vgg_face_weights.h5.tar.gz.gz -
3. Face Recognition using WebCam & Identifying Friends TV Show Characters in Video.html -
1. Chapter Introduction.mp4 -
1. Chapter Introduction.srt -
2. Alternative Frameworks PyTorch, MXNet, Caffe, Theano & OpenVINO.mp4 -
2. Alternative Frameworks PyTorch, MXNet, Caffe, Theano & OpenVINO.srt -
3. Popular APIs Google, Microsoft, ClarifAI Amazon Rekognition and others.mp4 -
3. Popular APIs Google, Microsoft, ClarifAI Amazon Rekognition and others.srt -
4. Popular Computer Vision Conferences & Finding Datasets.mp4 -
4. Popular Computer Vision Conferences & Finding Datasets.srt -
5. Building a Deep Learning Machine vs. Cloud GPUs.mp4 -
5. Building a Deep Learning Machine vs. Cloud GPUs.srt -
1. Step 1 - Creating a Credit Card Number Dataset.html -
1.1 Credit-Card Number Identification.zip.zip -
2. Step 2 - Training Our Model.html -
3. Step 3 - Extracting A Credit Card from the Background.html -
4. Step 4 - Use our Model to Identify the Digits & Display it onto our Credit Card.html -
1. Why use Cloud GPUs and How to Setup a PaperSpace Gradient Notebook.html -
2. Train a AlexNet on PaperSpace.html -
2.1 AlexNet CIFAR10.zip.zip -
1. Install and Run Flask.html -
1.1 CVApiWebAPp.tar.gz.gz -
2. Running Your Computer Vision Web App on Flask Locally.html -
3. Running Your Computer Vision API.html -
4. Setting Up An AWS Account.html -
5. Setting Up Your AWS EC2 Instance & Installing Keras, TensorFlow, OpenCV & Flask.html -
6. Changing your EC2 Security Group.html -
7. Using FileZilla to transfer files to your EC2 Instance.html -
8. Running your CV Web App on EC2.html -
9. Running your CV API on EC2.html -
1. Setting up your Deep Learning Virtual Machine (Download Code, VM & Slides here!).mp4 -
1. Setting up your Deep Learning Virtual Machine (Download Code, VM & Slides here!).srt -
1.1 Download Your Deep Learning Virtual Machine HERE.html -
1.2 DeepLearningCV2.tar.gz.gz -
1.3 Master Deep Learning Computer Vision Slides.pdf.pdf -
1.4 MIRROR - Download Your Deep Learning Virtual Machine HERE.html -
1.5 Slides - Deep-Learning-Computer-Vision.pdf.pdf -
2. Optional - Troubleshooting Guide for VM Setup & for resolving some MacOS Issues.html -
3. Optional - Manual Setup of Ubuntu Virtual Machine.html -
4. Optional - Setting up a shared drive with your Host OS.html -
1. Get Started! Handwriting Recognition, Simple Object Classification OpenCV Demo.mp4 -
1. Get Started! Handwriting Recognition, Simple Object Classification OpenCV Demo.srt -
2. Experiment with a Handwriting Classifier.mp4 -
2. Experiment with a Handwriting Classifier.srt -
3. Experiment with a Image Classifier.mp4 -
3. Experiment with a Image Classifier.srt -
4. OpenCV Demo – Live Sketch with Webcam.mp4 -
4. OpenCV Demo – Live Sketch with Webcam.srt -
1. Setup OpenCV.mp4 -
1. Setup OpenCV.srt -
1.1 MasterOpenCV.tar.gz.gz -
10. Transformations, Affine And Non-Affine - The Many Ways We Can Change Images.mp4 -
10. Transformations, Affine And Non-Affine - The Many Ways We Can Change Images.srt -
11. Image Translations - Moving Images Up, Down. Left And Right.mp4 -
11. Image Translations - Moving Images Up, Down. Left And Right.srt -
12. Rotations - How To Spin Your Image Around And Do Horizontal Flipping.mp4 -
12. Rotations - How To Spin Your Image Around And Do Horizontal Flipping.srt -
13. Scaling, Re-sizing and Interpolations - Understand How Re-Sizing Affects Quality.mp4 -
13. Scaling, Re-sizing and Interpolations - Understand How Re-Sizing Affects Quality.srt -
14. Image Pyramids - Another Way of Re-Sizing.mp4 -
14. Image Pyramids - Another Way of Re-Sizing.srt -
15. Cropping - Cut Out The Image The Regions You Want or Don't Want.mp4 -
15. Cropping - Cut Out The Image The Regions You Want or Don't Want.srt -
16. Arithmetic Operations - Brightening and Darkening Images.mp4 -
16. Arithmetic Operations - Brightening and Darkening Images.srt -
17. Bitwise Operations - How Image Masking Works.mp4 -
17. Bitwise Operations - How Image Masking Works.srt -
18. Blurring - The Many Ways We Can Blur Images & Why It's Important.mp4 -
18. Blurring - The Many Ways We Can Blur Images & Why It's Important.srt -
19. Sharpening - Reverse Your Images Blurs.mp4 -
19. Sharpening - Reverse Your Images Blurs.srt -
2. What are Images.mp4 -
2. What are Images.srt -
20. Thresholding (Binarization) - Making Certain Images Areas Black or White.mp4 -
20. Thresholding (Binarization) - Making Certain Images Areas Black or White.srt -
21. Dilation, Erosion, OpeningClosing - Importance of ThickeningThinning Lines.mp4 -
21. Dilation, Erosion, OpeningClosing - Importance of ThickeningThinning Lines.srt -
22. Edge Detection using Image Gradients & Canny Edge Detection.mp4 -
22. Edge Detection using Image Gradients & Canny Edge Detection.srt -
23. Perspective & Affine Transforms - Take An Off Angle Shot & Make It Look Top Down.mp4 -
23. Perspective & Affine Transforms - Take An Off Angle Shot & Make It Look Top Down.srt -
24. Mini Project 1 - Live Sketch App - Turn your Webcam Feed Into A Pencil Drawing.mp4 -
24. Mini Project 1 - Live Sketch App - Turn your Webcam Feed Into A Pencil Drawing.srt -
25. Segmentation and Contours - Extract Defined Shapes In Your Image.mp4 -
25. Segmentation and Contours - Extract Defined Shapes In Your Image.srt -
26. Sorting Contours - Sort Those Shapes By Size.mp4 -
26. Sorting Contours - Sort Those Shapes By Size.srt -
27. Approximating Contours & Finding Their Convex Hull - Clean Up Messy Contours.mp4 -
27. Approximating Contours & Finding Their Convex Hull - Clean Up Messy Contours.srt -
28. Matching Contour Shapes - Match Shapes In Images Even When Distorted.mp4 -
28. Matching Contour Shapes - Match Shapes In Images Even When Distorted.srt -
29. Mini Project 2 - Identify Shapes (Square, Rectangle, Circle, Triangle & Stars).mp4 -
29. Mini Project 2 - Identify Shapes (Square, Rectangle, Circle, Triangle & Stars).srt -
3. How are Images Formed.mp4 -
3. How are Images Formed.srt -
30. Line Detection - Detect Straight Lines E.g. The Lines On A Sudoku Game.mp4 -
30. Line Detection - Detect Straight Lines E.g. The Lines On A Sudoku Game.srt -
31. Circle Detection.html -
32. Blob Detection - Detect The Center of Flowers.mp4 -
32. Blob Detection - Detect The Center of Flowers.srt -
33. Mini Project 3 - Counting Circles and Ellipses.mp4 -
33. Mini Project 3 - Counting Circles and Ellipses.srt -
34. Object Detection Overview.mp4 -
34. Object Detection Overview.srt -
35. Mini Project # 4 - Finding Waldo (Quickly Find A Specific Pattern In An Image).mp4 -
35. Mini Project # 4 - Finding Waldo (Quickly Find A Specific Pattern In An Image).srt -
36. Feature Description Theory - How We Digitally Represent Objects.mp4 -
36. Feature Description Theory - How We Digitally Represent Objects.srt -
37. Finding Corners - Why Corners In Images Are Important to Object Detection.mp4 -
37. Finding Corners - Why Corners In Images Are Important to Object Detection.srt -
38. Histogram of Oriented Gradients - Another Novel Way Of Representing Images.mp4 -
38. Histogram of Oriented Gradients - Another Novel Way Of Representing Images.srt -
39. HAAR Cascade Classifiers - Learn How Classifiers Work And Why They're Amazing.mp4 -
39. HAAR Cascade Classifiers - Learn How Classifiers Work And Why They're Amazing.srt -
4. Storing Images on Computers.mp4 -
4. Storing Images on Computers.srt -
40. Face and Eye Detection - Detect Human Faces and Eyes In Any Image.mp4 -
40. Face and Eye Detection - Detect Human Faces and Eyes In Any Image.srt -
40.1 Lecture 6.2 and 6.3.tar.gz.gz -
41. Mini Project 6 - Car and Pedestrian Detection in Videos.mp4 -
41. Mini Project 6 - Car and Pedestrian Detection in Videos.srt -
41.1 Lecture 6.2 and 6.3.tar.gz.gz -
5. Getting Started with OpenCV - A Brief OpenCV Intro.mp4 -
5. Getting Started with OpenCV - A Brief OpenCV Intro.srt -
6. Grayscaling - Converting Color Images To Shades of Gray.mp4 -
6. Grayscaling - Converting Color Images To Shades of Gray.srt -
7. Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally.mp4 -
7. Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally.srt -
8. Histogram representation of Images - Visualizing the Components of Images.mp4 -
8. Histogram representation of Images - Visualizing the Components of Images.srt -
9. Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text.mp4 -
9. Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text.srt -
1. Neural Networks Chapter Overview.mp4 -
1. Neural Networks Chapter Overview.srt -
10. Epochs, Iterations and Batch Sizes.mp4 -
10. Epochs, Iterations and Batch Sizes.srt -
11. Measuring Performance and the Confusion Matrix.mp4 -
11. Measuring Performance and the Confusion Matrix.srt -
12. Review and Best Practices.mp4 -
12. Review and Best Practices.srt -
2. Machine Learning Overview.mp4 -
2. Machine Learning Overview.srt -
3. Neural Networks Explained.mp4 -
3. Neural Networks Explained.srt -
4. Forward Propagation.mp4 -
4. Forward Propagation.srt -
5. Activation Functions.mp4 -
5. Activation Functions.srt -
6. Training Part 1 – Loss Functions.mp4 -
6. Training Part 1 – Loss Functions.srt -
7. Training Part 2 – Backpropagation and Gradient Descent.mp4 -
7. Training Part 2 – Backpropagation and Gradient Descent.srt -
8. Backpropagation & Learning Rates – A Worked Example.mp4 -
8. Backpropagation & Learning Rates – A Worked Example.srt -
9. Regularization, Overfitting, Generalization and Test Datasets.mp4 -
9. Regularization, Overfitting, Generalization and Test Datasets.srt -
1. Convolutional Neural Networks Chapter Overview.mp4 -
1. Convolutional Neural Networks Chapter Overview.srt -
2. Convolutional Neural Networks Introduction.mp4 -
2. Convolutional Neural Networks Introduction.srt -
3. Convolutions & Image Features.mp4 -
3. Convolutions & Image Features.srt -
4. Depth, Stride and Padding.mp4 -
4. Depth, Stride and Padding.srt -
5. ReLU.mp4 -
5. ReLU.srt -
6. Pooling.mp4 -
6. Pooling.srt -
7. The Fully Connected Layer.mp4 -
7. The Fully Connected Layer.srt -
8. Training CNNs.mp4 -
8. Training CNNs.srt -
9. Designing Your Own CNN.mp4 -
9. Designing Your Own CNN.srt -
1. Building a CNN in Keras.mp4 -
1. Building a CNN in Keras.srt -
10. Saving and Loading Your Model.mp4 -
10. Saving and Loading Your Model.srt -
11. Displaying Your Model Visually.mp4 -
11. Displaying Your Model Visually.srt -
12. Building a Simple Image Classifier using CIFAR10.mp4 -
12. Building a Simple Image Classifier using CIFAR10.srt -
2. Introduction to Keras & Tensorflow.mp4 -
2. Introduction to Keras & Tensorflow.srt -
3. Building a Handwriting Recognition CNN.mp4 -
3. Building a Handwriting Recognition CNN.srt -
4. Loading Our Data.mp4 -
4. Loading Our Data.srt -
5. Getting our data in ‘Shape’.mp4 -
5. Getting our data in ‘Shape’.srt -
6. Hot One Encoding.mp4 -
6. Hot One Encoding.srt -
7. Building & Compiling Our Model.mp4 -
7. Building & Compiling Our Model.srt -
8. Training Our Classifier.mp4 -
8. Training Our Classifier.srt -
9. Plotting Loss and Accuracy Charts.mp4 -
9. Plotting Loss and Accuracy Charts.srt -
1. Introduction to Visualizing What CNNs 'see' & Filter Visualizations.mp4 -
1. Introduction to Visualizing What CNNs 'see' & Filter Visualizations.srt -
2. Saliency Maps & Class Activation Maps.mp4 -
2. Saliency Maps & Class Activation Maps.srt -
3. Saliency Maps & Class Activation Maps.mp4 -
3. Saliency Maps & Class Activation Maps.srt -
4. Filter Visualizations.mp4 -
4. Filter Visualizations.srt -
5. Heat Map Visualizations of Class Activations.mp4 -
5. Heat Map Visualizations of Class Activations.srt -
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[CourseClub.ME].url -
122 bytes
[FCS Forum].url -
133 bytes
[FreeCourseSite.com].url -
127 bytes
1. Course Introduction.mp4 -
90.2 MB
1. Course Introduction.srt -
15.7 KB
1. Data Augmentation Chapter Overview.mp4 -
3.9 MB
1. Data Augmentation Chapter Overview.srt -
1.5 KB
2. Splitting Data into Test and Training Datasets.mp4 -
103.8 MB
2. Splitting Data into Test and Training Datasets.srt -
14.3 KB
2.1 datasets.zip.zip -
65.7 MB
3. Train a Cats vs. Dogs Classifier.mp4 -
44.8 MB
3. Train a Cats vs. Dogs Classifier.srt -
6.2 KB
4. Boosting Accuracy with Data Augmentation.mp4 -
43.5 MB
4. Boosting Accuracy with Data Augmentation.srt -
7.4 KB
5. Types of Data Augmentation.mp4 -
52.5 MB
5. Types of Data Augmentation.srt -
8.3 KB
1. Introduction to the Confusion Matrix & Viewing Misclassifications.mp4 -
2.5 MB
1. Introduction to the Confusion Matrix & Viewing Misclassifications.srt -
917 bytes
2. Understanding the Confusion Matrix.mp4 -
93.0 MB
2. Understanding the Confusion Matrix.srt -
16.5 KB
3. Finding and Viewing Misclassified Data.mp4 -
44.4 MB
3. Finding and Viewing Misclassified Data.srt -
8.5 KB
1. Introduction to the types of Optimizers, Learning Rates & Callbacks.mp4 -
3.4 MB
1. Introduction to the types of Optimizers, Learning Rates & Callbacks.srt -
1.0 KB
2. Types Optimizers and Adaptive Learning Rate Methods.mp4 -
67.2 MB
2. Types Optimizers and Adaptive Learning Rate Methods.srt -
11.0 KB
3. Keras Callbacks and Checkpoint, Early Stopping and Adjust Learning Rates that Pl.mp4 -
51.1 MB
3. Keras Callbacks and Checkpoint, Early Stopping and Adjust Learning Rates that Pl.srt -
9.4 KB
4. Build a Fruit Classifier.mp4 -
92.9 MB
4. Build a Fruit Classifier.srt -
11.6 KB
4.1 fruits-360.tar.gz.gz -
376.0 MB
1. Intro to Building LeNet, AlexNet in Keras & Understand Batch Normalization.mp4 -
2.8 MB
1. Intro to Building LeNet, AlexNet in Keras & Understand Batch Normalization.srt -
860 bytes
2. Build LeNet and test on MNIST.mp4 -
32.1 MB
2. Build LeNet and test on MNIST.srt -
4.4 KB
3. Build AlexNet and test on CIFAR10.mp4 -
42.2 MB
3. Build AlexNet and test on CIFAR10.srt -
6.3 KB
4. Batch Normalization.mp4 -
23.2 MB
4. Batch Normalization.srt -
4.2 KB
5. Build a Clothing & Apparel Classifier (Fashion MNIST).mp4 -
56.3 MB
5. Build a Clothing & Apparel Classifier (Fashion MNIST).srt -
8.4 KB
5.1 fashion_mnist.tar.gz.gz -
29.4 MB
1. Chapter Introduction.mp4 -
2.9 MB
1. Chapter Introduction.srt -
856 bytes
2. ImageNet - Experimenting with pre-trained Models in Keras (VGG16, ResNet50, Mobi.mp4 -
82.1 MB
2. ImageNet - Experimenting with pre-trained Models in Keras (VGG16, ResNet50, Mobi.srt -
12.1 KB
3. Understanding VGG16 and VGG19.mp4 -
14.4 MB
3. Understanding VGG16 and VGG19.srt -
2.4 KB
4. Understanding ResNet50.mp4 -
9.8 MB
4. Understanding ResNet50.srt -
2.1 KB
5. Understanding InceptionV3.mp4 -
14.4 MB
5. Understanding InceptionV3.srt -
3.5 KB
1. Chapter Introduction.mp4 -
2.3 MB
1. Chapter Introduction.srt -
813 bytes
2. What is Transfer Learning and Fine Tuning.mp4 -
44.9 MB
2. What is Transfer Learning and Fine Tuning.srt -
9.3 KB
3. Build a Monkey Breed Classifier with MobileNet using Transfer Learning.mp4 -
135.3 MB
3. Build a Monkey Breed Classifier with MobileNet using Transfer Learning.srt -
17.6 KB
3.1 17_flowers.tar.gz.gz -
57.5 MB
4. Build a Flower Classifier with VGG16 using Transfer Learning.mp4 -
82.0 MB
4. Build a Flower Classifier with VGG16 using Transfer Learning.srt -
10.6 KB
4.1 monkey_breed.zip.zip -
546.7 MB
1. Chapter Introduction.mp4 -
1.9 MB
1. Chapter Introduction.srt -
636 bytes
2. Introducing LittleVGG.mp4 -
11.5 MB
2. Introducing LittleVGG.srt -
2.0 KB
3. Simpsons Character Recognition using LittleVGG.mp4 -
99.6 MB
3. Simpsons Character Recognition using LittleVGG.srt -
12.6 KB
3.1 simpsons.tar.gz.gz -
549.5 MB
1. Chapter Introduction.mp4 -
2.1 MB
1. Chapter Introduction.srt -
659 bytes
2. Dying ReLU Problem and Introduction to Leaky ReLU, ELU and PReLUs.mp4 -
32.3 MB
2. Dying ReLU Problem and Introduction to Leaky ReLU, ELU and PReLUs.srt -
6.7 KB
3. Advanced Initializations.mp4 -
15.0 MB
3. Advanced Initializations.srt -
3.6 KB
1. Chapter Introduction.mp4 -
4.6 MB
1. Chapter Introduction.srt -
1.3 KB
2. Build an Emotion, Facial Expression Detector.mp4 -
202.0 MB
2. Build an Emotion, Facial Expression Detector.srt -
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2.1 fer2013.zip.zip -
143.3 MB
3. Build EmotionAgeGender Recognition in our Deep Surveillance Monitor.mp4 -
260.8 MB
3. Build EmotionAgeGender Recognition in our Deep Surveillance Monitor.srt -
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3.1 age-gender-estimation.tar.gz.gz -
552.2 MB
1. Chapter Overview on Image Segmentation & Medical Imaging in U-Net.mp4 -
2.9 MB
1. Chapter Overview on Image Segmentation & Medical Imaging in U-Net.srt -
891 bytes
2. What is Segmentation And Applications in Medical Imaging.mp4 -
29.6 MB
2. What is Segmentation And Applications in Medical Imaging.srt -
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3. U-Net Image Segmentation with CNNs.mp4 -
30.5 MB
3. U-Net Image Segmentation with CNNs.srt -
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4. The Intersection over Union (IoU) Metric.mp4 -
43.0 MB
4. The Intersection over Union (IoU) Metric.srt -
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5. Finding the Nuclei in Divergent Images.mp4 -
171.1 MB
5. Finding the Nuclei in Divergent Images.srt -
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5.1 U_NET.zip.zip -
90.0 MB
1. Introduction to Computer Vision & Deep Learning.mp4 -
3.1 MB
1. Introduction to Computer Vision & Deep Learning.srt -
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2. What is Computer Vision and What Makes it Hard.mp4 -
60.1 MB
2. What is Computer Vision and What Makes it Hard.srt -
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3. What are Images.mp4 -
58.8 MB
3. What are Images.srt -
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4. Intro to OpenCV, OpenVINO™ & their Limitations.mp4 -
41.4 MB
4. Intro to OpenCV, OpenVINO™ & their Limitations.srt -
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1. Chapter Introduction.mp4 -
3.4 MB
1. Chapter Introduction.srt -
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2. Object Detection Introduction - Sliding Windows with HOGs.mp4 -
51.6 MB
2. Object Detection Introduction - Sliding Windows with HOGs.srt -
7.7 KB
3. R-CNN, Fast R-CNN, Faster R-CNN and Mask R-CNN.mp4 -
135.9 MB
3. R-CNN, Fast R-CNN, Faster R-CNN and Mask R-CNN.srt -
21.0 KB
4. Single Shot Detectors (SSDs).mp4 -
12.4 MB
4. Single Shot Detectors (SSDs).srt -
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5. YOLO to YOLOv3.mp4 -
33.1 MB
5. YOLO to YOLOv3.srt -
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1. Chapter Introduction.mp4 -
2.4 MB
1. Chapter Introduction.srt -
765 bytes
2. TFOD API Install and Setup.mp4 -
47.6 MB
2. TFOD API Install and Setup.srt -
6.6 KB
2.1 Download the code (for those not using the Virtual Machine).html -
108 bytes
3. Experiment with a ResNet SSD on images, webcam and videos.mp4 -
83.6 MB
3. Experiment with a ResNet SSD on images, webcam and videos.srt -
10.1 KB
4. How to Train a TFOD Model.mp4 -
74.2 MB
4. How to Train a TFOD Model.srt -
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1. Chapter Introduction.mp4 -
2.5 MB
1. Chapter Introduction.srt -
658 bytes
2. Setting up and install Yolo DarkNet and DarkFlow.mp4 -
51.7 MB
2. Setting up and install Yolo DarkNet and DarkFlow.srt -
7.6 KB
2.1 Guide to the MacOS Install.html -
124 bytes
2.2 Download the YOLO files (if not using the VM).html -
108 bytes
3. Experiment with YOLO on still images, webcam and videos.mp4 -
104.5 MB
3. Experiment with YOLO on still images, webcam and videos.srt -
12.1 KB
4. Build your own YOLO Object Detector - Detecting London Underground Signs.mp4 -
159.1 MB
4. Build your own YOLO Object Detector - Detecting London Underground Signs.srt -
22.3 KB
4.1 LondonUnderground_train.tar.gz.gz -
5.1 MB
1. Chapter Introduction.mp4 -
1.5 MB
1. Chapter Introduction.srt -
496 bytes
2. DeepDream – How AI Generated Art All Started.mp4 -
84.0 MB
2. DeepDream – How AI Generated Art All Started.srt -
11.4 KB
3. Neural Style Transfer.mp4 -
124.7 MB
3. Neural Style Transfer.srt -
17.3 KB
1. Generative Adverserial Neural Networks Chapter Overview.mp4 -
4.6 MB
1. Generative Adverserial Neural Networks Chapter Overview.srt -
1.2 KB
2. Introduction To GANs.mp4 -
85.3 MB
2. Introduction To GANs.srt -
16.6 KB
3. Mathematics of GANs.mp4 -
27.2 MB
3. Mathematics of GANs.srt -
5.2 KB
4. Implementing GANs in Keras.mp4 -
96.3 MB
4. Implementing GANs in Keras.srt -
15.6 KB
5. Face Aging GAN.mp4 -
46.8 MB
5. Face Aging GAN.srt -
7.5 KB
5.1 GenerativeNetworks.tar.gz.gz -
117.0 MB
1. Basic Face Recognition using LittleVGG CNN.html -
997 bytes
1.1 25. Face Recognition All Notebooks.tar.gz.gz -
120.7 MB
2. Face Matching with VGGFace.html -
1.1 KB
2.1 vgg_face_weights.h5.tar.gz.gz -
520.7 MB
3. Face Recognition using WebCam & Identifying Friends TV Show Characters in Video.html -
441 bytes
1. Chapter Introduction.mp4 -
3.2 MB
1. Chapter Introduction.srt -
1.0 KB
2. Alternative Frameworks PyTorch, MXNet, Caffe, Theano & OpenVINO.mp4 -
23.0 MB
2. Alternative Frameworks PyTorch, MXNet, Caffe, Theano & OpenVINO.srt -
4.6 KB
3. Popular APIs Google, Microsoft, ClarifAI Amazon Rekognition and others.mp4 -
8.6 MB
3. Popular APIs Google, Microsoft, ClarifAI Amazon Rekognition and others.srt -
1.6 KB
4. Popular Computer Vision Conferences & Finding Datasets.mp4 -
19.6 MB
4. Popular Computer Vision Conferences & Finding Datasets.srt -
3.5 KB
5. Building a Deep Learning Machine vs. Cloud GPUs.mp4 -
28.2 MB
5. Building a Deep Learning Machine vs. Cloud GPUs.srt -
5.6 KB
1. Step 1 - Creating a Credit Card Number Dataset.html -
12.3 KB
1.1 Credit-Card Number Identification.zip.zip -
128.4 KB
2. Step 2 - Training Our Model.html -
4.7 KB
3. Step 3 - Extracting A Credit Card from the Background.html -
8.0 KB
4. Step 4 - Use our Model to Identify the Digits & Display it onto our Credit Card.html -
4.1 KB
1. Why use Cloud GPUs and How to Setup a PaperSpace Gradient Notebook.html -
15.0 KB
2. Train a AlexNet on PaperSpace.html -
6.9 KB
2.1 AlexNet CIFAR10.zip.zip -
29.6 KB
1. Install and Run Flask.html -
5.0 KB
1.1 CVApiWebAPp.tar.gz.gz -
7.7 MB
2. Running Your Computer Vision Web App on Flask Locally.html -
6.7 KB
3. Running Your Computer Vision API.html -
4.8 KB
4. Setting Up An AWS Account.html -
1.7 KB
5. Setting Up Your AWS EC2 Instance & Installing Keras, TensorFlow, OpenCV & Flask.html -
6.9 KB
6. Changing your EC2 Security Group.html -
1.6 KB
7. Using FileZilla to transfer files to your EC2 Instance.html -
4.7 KB
8. Running your CV Web App on EC2.html -
2.4 KB
9. Running your CV API on EC2.html -
3.1 KB
1. Setting up your Deep Learning Virtual Machine (Download Code, VM & Slides here!).mp4 -
77.4 MB
1. Setting up your Deep Learning Virtual Machine (Download Code, VM & Slides here!).srt -
14.4 KB
1.1 Download Your Deep Learning Virtual Machine HERE.html -
143 bytes
1.2 DeepLearningCV2.tar.gz.gz -
643.2 MB
1.3 Master Deep Learning Computer Vision Slides.pdf.pdf -
56.5 MB
1.4 MIRROR - Download Your Deep Learning Virtual Machine HERE.html -
108 bytes
1.5 Slides - Deep-Learning-Computer-Vision.pdf.pdf -
56.5 MB
2. Optional - Troubleshooting Guide for VM Setup & for resolving some MacOS Issues.html -
6.7 KB
3. Optional - Manual Setup of Ubuntu Virtual Machine.html -
3.5 KB
4. Optional - Setting up a shared drive with your Host OS.html -
2.9 KB
1. Get Started! Handwriting Recognition, Simple Object Classification OpenCV Demo.mp4 -
7.5 MB
1. Get Started! Handwriting Recognition, Simple Object Classification OpenCV Demo.srt -
900 bytes
2. Experiment with a Handwriting Classifier.mp4 -
67.3 MB
2. Experiment with a Handwriting Classifier.srt -
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3. Experiment with a Image Classifier.mp4 -
27.3 MB
3. Experiment with a Image Classifier.srt -
4.3 KB
4. OpenCV Demo – Live Sketch with Webcam.mp4 -
41.2 MB
4. OpenCV Demo – Live Sketch with Webcam.srt -
5.5 KB
1. Setup OpenCV.mp4 -
13.9 MB
1. Setup OpenCV.srt -
2.2 KB
1.1 MasterOpenCV.tar.gz.gz -
47.1 MB
10. Transformations, Affine And Non-Affine - The Many Ways We Can Change Images.mp4 -
11.0 MB
10. Transformations, Affine And Non-Affine - The Many Ways We Can Change Images.srt -
3.4 KB
11. Image Translations - Moving Images Up, Down. Left And Right.mp4 -
18.5 MB
11. Image Translations - Moving Images Up, Down. Left And Right.srt -
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12. Rotations - How To Spin Your Image Around And Do Horizontal Flipping.mp4 -
23.1 MB
12. Rotations - How To Spin Your Image Around And Do Horizontal Flipping.srt -
4.6 KB
13. Scaling, Re-sizing and Interpolations - Understand How Re-Sizing Affects Quality.mp4 -
36.6 MB
13. Scaling, Re-sizing and Interpolations - Understand How Re-Sizing Affects Quality.srt -
6.6 KB
14. Image Pyramids - Another Way of Re-Sizing.mp4 -
14.2 MB
14. Image Pyramids - Another Way of Re-Sizing.srt -
2.8 KB
15. Cropping - Cut Out The Image The Regions You Want or Don't Want.mp4 -
24.1 MB
15. Cropping - Cut Out The Image The Regions You Want or Don't Want.srt -
3.9 KB
16. Arithmetic Operations - Brightening and Darkening Images.mp4 -
31.1 MB
16. Arithmetic Operations - Brightening and Darkening Images.srt -
16.5 MB
17. Bitwise Operations - How Image Masking Works.mp4 -
28.9 MB
17. Bitwise Operations - How Image Masking Works.srt -
5.7 KB
18. Blurring - The Many Ways We Can Blur Images & Why It's Important.mp4 -
70.2 MB
18. Blurring - The Many Ways We Can Blur Images & Why It's Important.srt -
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19. Sharpening - Reverse Your Images Blurs.mp4 -
17.3 MB
19. Sharpening - Reverse Your Images Blurs.srt -
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2. What are Images.mp4 -
16.0 MB
2. What are Images.srt -
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20. Thresholding (Binarization) - Making Certain Images Areas Black or White.mp4 -
64.8 MB
20. Thresholding (Binarization) - Making Certain Images Areas Black or White.srt -
12.2 KB
21. Dilation, Erosion, OpeningClosing - Importance of ThickeningThinning Lines.mp4 -
42.0 MB
21. Dilation, Erosion, OpeningClosing - Importance of ThickeningThinning Lines.srt -
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22. Edge Detection using Image Gradients & Canny Edge Detection.mp4 -
45.7 MB
22. Edge Detection using Image Gradients & Canny Edge Detection.srt -
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23. Perspective & Affine Transforms - Take An Off Angle Shot & Make It Look Top Down.mp4 -
31.7 MB
23. Perspective & Affine Transforms - Take An Off Angle Shot & Make It Look Top Down.srt -
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24. Mini Project 1 - Live Sketch App - Turn your Webcam Feed Into A Pencil Drawing.mp4 -
43.8 MB
24. Mini Project 1 - Live Sketch App - Turn your Webcam Feed Into A Pencil Drawing.srt -
7.5 KB
25. Segmentation and Contours - Extract Defined Shapes In Your Image.mp4 -
77.4 MB
25. Segmentation and Contours - Extract Defined Shapes In Your Image.srt -
16.7 KB
26. Sorting Contours - Sort Those Shapes By Size.mp4 -
106.2 MB
26. Sorting Contours - Sort Those Shapes By Size.srt -
19.9 KB
27. Approximating Contours & Finding Their Convex Hull - Clean Up Messy Contours.mp4 -
47.0 MB
27. Approximating Contours & Finding Their Convex Hull - Clean Up Messy Contours.srt -
36.1 MB
28. Matching Contour Shapes - Match Shapes In Images Even When Distorted.mp4 -
52.9 MB
28. Matching Contour Shapes - Match Shapes In Images Even When Distorted.srt -
7.9 KB
29. Mini Project 2 - Identify Shapes (Square, Rectangle, Circle, Triangle & Stars).mp4 -
47.3 MB
29. Mini Project 2 - Identify Shapes (Square, Rectangle, Circle, Triangle & Stars).srt -
8.3 KB
3. How are Images Formed.mp4 -
21.3 MB
3. How are Images Formed.srt -
45.8 MB
30. Line Detection - Detect Straight Lines E.g. The Lines On A Sudoku Game.mp4 -
65.7 MB
30. Line Detection - Detect Straight Lines E.g. The Lines On A Sudoku Game.srt -
9.9 KB
31. Circle Detection.html -
1.6 KB
32. Blob Detection - Detect The Center of Flowers.mp4 -
32.2 MB
32. Blob Detection - Detect The Center of Flowers.srt -
5.2 KB
33. Mini Project 3 - Counting Circles and Ellipses.mp4 -
51.9 MB
33. Mini Project 3 - Counting Circles and Ellipses.srt -
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34. Object Detection Overview.mp4 -
30.8 MB
34. Object Detection Overview.srt -
4.9 KB
35. Mini Project # 4 - Finding Waldo (Quickly Find A Specific Pattern In An Image).mp4 -
25.9 MB
35. Mini Project # 4 - Finding Waldo (Quickly Find A Specific Pattern In An Image).srt -
4.4 KB
36. Feature Description Theory - How We Digitally Represent Objects.mp4 -
35.3 MB
36. Feature Description Theory - How We Digitally Represent Objects.srt -
7.4 KB
37. Finding Corners - Why Corners In Images Are Important to Object Detection.mp4 -
52.1 MB
37. Finding Corners - Why Corners In Images Are Important to Object Detection.srt -
10.5 KB
38. Histogram of Oriented Gradients - Another Novel Way Of Representing Images.mp4 -
82.0 MB
38. Histogram of Oriented Gradients - Another Novel Way Of Representing Images.srt -
12.0 KB
39. HAAR Cascade Classifiers - Learn How Classifiers Work And Why They're Amazing.mp4 -
43.1 MB
39. HAAR Cascade Classifiers - Learn How Classifiers Work And Why They're Amazing.srt -
7.8 KB
4. Storing Images on Computers.mp4 -
42.3 MB
4. Storing Images on Computers.srt -
6.8 KB
40. Face and Eye Detection - Detect Human Faces and Eyes In Any Image.mp4 -
89.2 MB
40. Face and Eye Detection - Detect Human Faces and Eyes In Any Image.srt -
16.6 KB
40.1 Lecture 6.2 and 6.3.tar.gz.gz -
271.5 KB
41. Mini Project 6 - Car and Pedestrian Detection in Videos.mp4 -
56.4 MB
41. Mini Project 6 - Car and Pedestrian Detection in Videos.srt -
10.5 KB
41.1 Lecture 6.2 and 6.3.tar.gz.gz -
271.5 KB
5. Getting Started with OpenCV - A Brief OpenCV Intro.mp4 -
74.9 MB
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12.3 KB
6. Grayscaling - Converting Color Images To Shades of Gray.mp4 -
15.0 MB
6. Grayscaling - Converting Color Images To Shades of Gray.srt -
2.8 KB
7. Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally.mp4 -
106.2 MB
7. Understanding Color Spaces - The Many Ways Color Images Are Stored Digitally.srt -
16.9 KB
8. Histogram representation of Images - Visualizing the Components of Images.mp4 -
42.4 MB
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9. Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text.mp4 -
31.0 MB
9. Creating Images & Drawing on Images - Make Squares, Circles, Polygons & Add Text.srt -
5.5 KB
1. Neural Networks Chapter Overview.mp4 -
7.8 MB
1. Neural Networks Chapter Overview.srt -
2.1 KB
10. Epochs, Iterations and Batch Sizes.mp4 -
26.1 MB
10. Epochs, Iterations and Batch Sizes.srt -
4.8 KB
11. Measuring Performance and the Confusion Matrix.mp4 -
52.1 MB
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9.7 KB
12. Review and Best Practices.mp4 -
27.1 MB
12. Review and Best Practices.srt -
6.1 KB
2. Machine Learning Overview.mp4 -
52.3 MB
2. Machine Learning Overview.srt -
11.3 KB
3. Neural Networks Explained.mp4 -
23.3 MB
3. Neural Networks Explained.srt -
5.5 KB
4. Forward Propagation.mp4 -
63.3 MB
4. Forward Propagation.srt -
11.5 KB
5. Activation Functions.mp4 -
59.6 MB
5. Activation Functions.srt -
11.8 KB
6. Training Part 1 – Loss Functions.mp4 -
58.4 MB
6. Training Part 1 – Loss Functions.srt -
11.9 KB
7. Training Part 2 – Backpropagation and Gradient Descent.mp4 -
72.6 MB
7. Training Part 2 – Backpropagation and Gradient Descent.srt -
13.2 KB
8. Backpropagation & Learning Rates – A Worked Example.mp4 -
99.8 MB
8. Backpropagation & Learning Rates – A Worked Example.srt -
17.9 KB
9. Regularization, Overfitting, Generalization and Test Datasets.mp4 -
118.4 MB
9. Regularization, Overfitting, Generalization and Test Datasets.srt -
21.2 KB
1. Convolutional Neural Networks Chapter Overview.mp4 -
5.1 MB
1. Convolutional Neural Networks Chapter Overview.srt -
1.5 KB
2. Convolutional Neural Networks Introduction.mp4 -
36.7 MB
2. Convolutional Neural Networks Introduction.srt -
7.0 KB
3. Convolutions & Image Features.mp4 -
102.4 MB
3. Convolutions & Image Features.srt -
17.4 KB
4. Depth, Stride and Padding.mp4 -
46.5 MB
4. Depth, Stride and Padding.srt -
9.1 KB
5. ReLU.mp4 -
10.9 MB
5. ReLU.srt -
2.4 KB
6. Pooling.mp4 -
28.8 MB
6. Pooling.srt -
6.4 KB
7. The Fully Connected Layer.mp4 -
13.8 MB
7. The Fully Connected Layer.srt -
3.2 KB
8. Training CNNs.mp4 -
27.2 MB
8. Training CNNs.srt -
4.2 KB
9. Designing Your Own CNN.mp4 -
24.2 MB
9. Designing Your Own CNN.srt -
5.3 KB
1. Building a CNN in Keras.mp4 -
5.6 MB
1. Building a CNN in Keras.srt -
1.4 KB
10. Saving and Loading Your Model.mp4 -
29.5 MB
10. Saving and Loading Your Model.srt -
4.6 KB
11. Displaying Your Model Visually.mp4 -
25.4 MB
11. Displaying Your Model Visually.srt -
4.3 KB
12. Building a Simple Image Classifier using CIFAR10.mp4 -
74.3 MB
12. Building a Simple Image Classifier using CIFAR10.srt -
11.2 KB
2. Introduction to Keras & Tensorflow.mp4 -
73.7 MB
2. Introduction to Keras & Tensorflow.srt -
17.8 KB
3. Building a Handwriting Recognition CNN.mp4 -
11.1 MB
3. Building a Handwriting Recognition CNN.srt -
2.6 KB
4. Loading Our Data.mp4 -
52.9 MB
4. Loading Our Data.srt -
8.6 KB
5. Getting our data in ‘Shape’.mp4 -
33.8 MB
5. Getting our data in ‘Shape’.srt -
5.9 KB
6. Hot One Encoding.mp4 -
18.2 MB
6. Hot One Encoding.srt -
4.1 KB
7. Building & Compiling Our Model.mp4 -
36.2 MB
7. Building & Compiling Our Model.srt -
5.5 KB
8. Training Our Classifier.mp4 -
40.8 MB
8. Training Our Classifier.srt -
7.0 KB
9. Plotting Loss and Accuracy Charts.mp4 -
25.6 MB
9. Plotting Loss and Accuracy Charts.srt -
4.6 KB
1. Introduction to Visualizing What CNNs 'see' & Filter Visualizations.mp4 -
8.3 MB
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1.5 KB
2. Saliency Maps & Class Activation Maps.mp4 -
64.2 MB
2. Saliency Maps & Class Activation Maps.srt -
9.2 KB
3. Saliency Maps & Class Activation Maps.mp4 -
80.8 MB
3. Saliency Maps & Class Activation Maps.srt -
11.3 KB
4. Filter Visualizations.mp4 -
89.5 MB
4. Filter Visualizations.srt -
13.5 KB
5. Heat Map Visualizations of Class Activations.mp4 -
34.2 MB
5. Heat Map Visualizations of Class Activations.srt -
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