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Please note that this page does not hosts or makes available any of the listed filenames. You
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| 001. Convolution Revisited.mp4 |
27.19MB |
| 001. Course Overview.mp4 |
48.80MB |
| 001. Example Setup.mp4 |
23.67MB |
| 001. Gray-Scale Images.mp4 |
37.23MB |
| 001. Image Classification Revisited.mp4 |
20.46MB |
| 001. Introduction to Object Detection.mp4 |
35.74MB |
| 001. Introduction to TensorFlow.mp4 |
29.46MB |
| 001. LeNet.mp4 |
21.75MB |
| 001. Neuron and Perceptron.mp4 |
44.52MB |
| 001. Problem Setup.mp4 |
29.98MB |
| 001. Problem Setup.mp4 |
112.85MB |
| 001. What Is Transfer learning.mp4 |
26.36MB |
| 002. Classification Pipeline.mp4 |
43.89MB |
| 002. DNN Architecture.mp4 |
27.28MB |
| 002. FashionMNIST Example Plan Neural Network.mp4 |
89.38MB |
| 002. Gray-Scale Images Quiz.mp4 |
4.16MB |
| 002. Implementation TensorFlow Hub.mp4 |
42.59MB |
| 002. Implementing Convolution in Python Revisited.mp4 |
25.62MB |
| 002. Introduction to Instructor.mp4 |
13.68MB |
| 002. LeNet Quiz.mp4 |
6.22MB |
| 002. Project Implementation.mp4 |
71.52MB |
| 002. Sliding Window Object Localization.mp4 |
34.16MB |
| 002. Why Derivatives.mp4 |
38.93MB |
| 002. Why Transfer Learning.mp4 |
39.11MB |
| 003. Classification Pipeline Quiz.mp4 |
4.22MB |
| 003. DNN Architecture Quiz.mp4 |
5.79MB |
| 003. Face Verification Activity.mp4 |
4.61MB |
| 003. FashionMNIST Example CNN.mp4 |
95.32MB |
| 003. Gray-Scale Images Solution.mp4 |
4.91MB |
| 003. ImageNet Challenge.mp4 |
42.58MB |
| 003. LeNet Solution.mp4 |
8.68MB |
| 003. Sliding Window Efficient Implementation.mp4 |
27.16MB |
| 003. Thank You and Conclusion.mp4 |
12.31MB |
| 003. Why CNN.mp4 |
82.84MB |
| 003. Why Convolution.mp4 |
21.96MB |
| 003. Why Derivatives Quiz.mp4 |
5.35MB |
| 004. AlexNet.mp4 |
32.33MB |
| 004. Classification Pipeline Solution.mp4 |
5.19MB |
| 004. DNN Architecture Solution.mp4 |
7.13MB |
| 004. Filters Padding Strides.mp4 |
27.92MB |
| 004. Focus of the Course.mp4 |
21.93MB |
| 004. Introduction to TensorFlow Activity.mp4 |
4.94MB |
| 004. Practical Tips.mp4 |
22.70MB |
| 004. RGB Images.mp4 |
30.38MB |
| 004. Why Derivatives Solution.mp4 |
11.01MB |
| 004. YOLO Introduction.mp4 |
34.72MB |
| 005. FeedForward FullyConnected MLP.mp4 |
16.69MB |
| 005. Padding Image.mp4 |
30.90MB |
| 005. Project in TensorFlow.mp4 |
149.67MB |
| 005. RGB Images Quiz.mp4 |
4.60MB |
| 005. Sliding Window Implementation.mp4 |
24.97MB |
| 005. VGG.mp4 |
19.01MB |
| 005. What Is Chain Rule.mp4 |
29.53MB |
| 005. YOLO Training Data Generation.mp4 |
26.96MB |
| 006. Applying Chain Rule.mp4 |
38.54MB |
| 006. Calculating Number of Weights of DNN.mp4 |
22.37MB |
| 006. InceptionNet.mp4 |
30.02MB |
| 006. Pooling Tensors.mp4 |
22.42MB |
| 006. RGB Images Solution.mp4 |
5.02MB |
| 006. Shift Scale Rotation Invariance.mp4 |
47.00MB |
| 006. Transfer Learning Activity.mp4 |
4.96MB |
| 006. YOLO Anchor Boxes.mp4 |
43.60MB |
| 007. Calculating Number of Weights of DNN Quiz.mp4 |
4.52MB |
| 007. CNN Example.mp4 |
23.00MB |
| 007. GoogLeNet.mp4 |
18.38MB |
| 007. Gradients of MaxPooling Layer.mp4 |
33.87MB |
| 007. Reading and Showing Images in Python.mp4 |
37.77MB |
| 007. Shift Scale Rotation Invariance Exercise.mp4 |
58.64MB |
| 007. YOLO Algorithm.mp4 |
29.52MB |
| 008. Calculating Number of Weights of DNN Solution.mp4 |
7.08MB |
| 008. Convolution and Pooling Details.mp4 |
26.97MB |
| 008. Gradients of MaxPooling Layer Quiz.mp4 |
5.83MB |
| 008. Person Detection.mp4 |
43.12MB |
| 008. Reading and Showing Images in Python Quiz.mp4 |
4.07MB |
| 008. Resnet.mp4 |
31.34MB |
| 008. YOLO Non-Maxima Suppression.mp4 |
32.63MB |
| 009. Classical CNNs Activity.mp4 |
4.85MB |
| 009. Gradients of MaxPooling Layer Solution.mp4 |
8.15MB |
| 009. HOG Features.mp4 |
38.04MB |
| 009. MaxPooling Exercise.mp4 |
11.68MB |
| 009. Number of Neurons Versus Number of Layers.mp4 |
25.11MB |
| 009. RCNN.mp4 |
12.44MB |
| 009. Reading and Showing Images in Python Solution.mp4 |
4.36MB |
| 010. Converting an Image to Grayscale in Python.mp4 |
29.93MB |
| 010. Discriminative Versus Generative Learning.mp4 |
22.61MB |
| 010. Gradients of Convolutional Layer.mp4 |
38.03MB |
| 010. HOG Features Exercise.mp4 |
28.57MB |
| 010. NonVectorized Implementations of Conv2d and Pool2d.mp4 |
69.20MB |
| 010. YOLO Activity.mp4 |
5.26MB |
| 011. Converting an Image to Grayscale in Python Quiz.mp4 |
4.43MB |
| 011. Deep Neural Network Architecture Activity.mp4 |
7.94MB |
| 011. Extending to Multiple Filters.mp4 |
16.04MB |
| 011. Hand Engineering Versus CNNs.mp4 |
30.05MB |
| 011. Universal Approximation Theorem.mp4 |
31.36MB |
| 012. Converting an Image to Grayscale in Python Solution.mp4 |
5.41MB |
| 012. Extending to Multiple Layers.mp4 |
27.43MB |
| 012. Object Detection Activity.mp4 |
18.48MB |
| 012. Why Depth.mp4 |
12.78MB |
| 013. Decision Boundary in DNN.mp4 |
22.09MB |
| 013. Extending to Multiple Layers Quiz.mp4 |
7.80MB |
| 013. Image Formation.mp4 |
19.38MB |
| 014. Decision Boundary in DNN Quiz.mp4 |
6.03MB |
| 014. Extending to Multiple Layers Solution.mp4 |
26.13MB |
| 014. Image Formation Quiz.mp4 |
4.45MB |
| 015. Decision Boundary in DNN Solution.mp4 |
12.91MB |
| 015. Image Formation Solution.mp4 |
4.48MB |
| 015. Implementation in NumPy ForwardPass.mp4 |
30.70MB |
| 016. BiasTerm.mp4 |
28.83MB |
| 016. Image Blurring 1.mp4 |
45.63MB |
| 016. Implementation in NumPy BackwardPass 1.mp4 |
24.99MB |
| 017. BiasTerm Quiz.mp4 |
4.50MB |
| 017. Image Blurring 1 Quiz.mp4 |
5.05MB |
| 017. Implementation in NumPy BackwardPass 2.mp4 |
17.09MB |
| 018. BiasTerm Solution.mp4 |
5.54MB |
| 018. Image Blurring 1 Solution.mp4 |
4.54MB |
| 018. Implementation in NumPy BackwardPass 3.mp4 |
32.59MB |
| 019. Activation Function.mp4 |
30.36MB |
| 019. Image Blurring 2.mp4 |
39.06MB |
| 019. Implementation in NumPy BackwardPass 4.mp4 |
49.57MB |
| 020. Activation Function Quiz.mp4 |
4.66MB |
| 020. Image Blurring 2 Quiz.mp4 |
4.42MB |
| 020. Implementation in NumPy BackwardPass 5.mp4 |
80.87MB |
| 021. Activation Function Solution.mp4 |
6.27MB |
| 021. Gradient Descent in CNNs Activity.mp4 |
7.77MB |
| 021. Image Blurring 2 Solution.mp4 |
5.32MB |
| 022. DNN Training Parameters.mp4 |
37.19MB |
| 022. General Image Filtering.mp4 |
19.17MB |
| 023. Convolution.mp4 |
22.76MB |
| 023. DNN Training Parameters Quiz.mp4 |
4.62MB |
| 024. DNN Training Parameters Solution.mp4 |
4.87MB |
| 024. Edge Detection.mp4 |
29.17MB |
| 025. Gradient Descent.mp4 |
29.02MB |
| 025. Image Sharpening.mp4 |
19.62MB |
| 026. Backpropagation.mp4 |
40.28MB |
| 026. Implementation of Image Blurring Edge Detection Image Sharpening in Python.mp4 |
65.01MB |
| 027. Parametric Shape Detection.mp4 |
34.16MB |
| 027. Training DNN Animation.mp4 |
22.43MB |
| 028. Image Processing.mp4 |
15.08MB |
| 028. Weight Initialization.mp4 |
45.00MB |
| 029. Image Processing Activity.mp4 |
10.83MB |
| 029. Weight Initialization Quiz.mp4 |
4.60MB |
| 030. Image Processing Activity Solution.mp4 |
44.55MB |
| 030. Weight Initialization Solution.mp4 |
5.60MB |
| 031. Batch MiniBatch Stochastic Gradient Descent.mp4 |
34.18MB |
| 032. Batch Normalization.mp4 |
22.01MB |
| 033. Rprop and Momentum.mp4 |
57.97MB |
| 034. Rprop and Momentum Quiz.mp4 |
6.01MB |
| 035. Rprop and Momentum Solution.mp4 |
6.52MB |
| 036. Convergence Animation.mp4 |
32.24MB |
| 037. DropOut, Early Stopping and Hyperparameters.mp4 |
51.08MB |
| 038. DropOut, Early Stopping and Hyperparameters Quiz.mp4 |
5.76MB |
| 039. DropOut, Early Stopping and Hyperparameters Solution.mp4 |
8.50MB |
| Bonus Resources.txt |
386B |
| Get Bonus Downloads Here.url |
183B |