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Convolutional Neural Networks with TensorFlow in Python
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[TutsNode.com] - Convolutional Neural Networks with TensorFlow in Python (Size: 2.21 GB) (Files: 109)
[TutsNode.com] - Convolutional Neural Networks with TensorFlow in Python
07 Tensorboard_ Visualization tool for TensorFlow
027 Confusion matrix and visualizing it with Tensorboard.mp4
026 Tensorboard on the MNIST example.en.srt
026 Tensorboard on the MNIST example.mp4
027 Confusion matrix and visualizing it with Tensorboard.en.srt
028 Using Tensorboard to tune hyperparameters.en.srt
028 Using Tensorboard to tune hyperparameters.mp4
external-assets-links.txt
01 Introduction to the course
001 What does the course cover_.en.srt
001 What does the course cover_.mp4
002 Why CNNs_.en.srt
002 Why CNNs_.mp4
02 Kernels
003 Introduction to image kernels.en.srt
003 Introduction to image kernels.mp4
004 How do image transformations work_.en.srt
004 How do image transformations work_.mp4
005 Kernels as matrices.en.srt
005 Kernels as matrices.mp4
006 Convolution - applying kernels.en.srt
006 Convolution - applying kernels.mp4
007 Edge handling.en.srt
007 Edge handling.mp4
03 CNN Introduction
008 CNNs motivation.en.srt
008 CNNs motivation.mp4
009 Feature maps.en.srt
009 Feature maps.mp4
010 Pooling and Stride.en.srt
010 Pooling and Stride.mp4
011 Dimensions.en.srt
011 Dimensions.mp4
04 Neural networks techniques (revision)
012 Activation functions.en.srt
012 Activation functions.mp4
013 Overfitting and early stopping.en.srt
013 Overfitting and early stopping.mp4
014 Optimizers.en.srt
014 Optimizers.mp4
05 Setting up the environment
015 Setting up the environment - Do not skip, please!.en.srt
015 Setting up the environment - Do not skip, please!.mp4
016 Why Python and why Jupyter_.en.srt
016 Why Python and why Jupyter_.mp4
017 Installing Anaconda.en.srt
017 Installing Anaconda.mp4
018 Jupyter Dashboard - Part 1.en.srt
018 Jupyter Dashboard - Part 1.mp4
019 Jupyter Dashboard - Part 2.en.srt
019 Jupyter Dashboard - Part 2.mp4
020 Installing the packages.en.srt
020 Installing the packages.mp4
06 CNN assembling - MNIST
021 Road plan.en.srt
021 Road plan.mp4
022 A simple CNN architecture.en.srt
022 A simple CNN architecture.mp4
023 Preprocessing the data.en.srt
023 Preprocessing the data.mp4
024 Building and training the CNN.en.srt
024 Building and training the CNN.mp4
025 Testing the trained CNN.en.srt
025 Testing the trained CNN.mp4
external-assets-links.txt
08 Common techniques for better performance of NN
029 Introduction.en.srt
029 Introduction.mp4
030 Regularization.en.srt
030 Regularization.mp4
031 L2 Regularization and Weight Decay.en.srt
031 L2 Regularization and Weight Decay.mp4
032 Dropout.en.srt
032 Dropout.mp4
033 Data augmentation.en.srt
033 Data augmentation.mp4
09 A practical project_ Labelling fashion items
034 Introduction to the problem.en.srt
034 Introduction to the problem.mp4
035 The objective and the images.en.srt
035 The objective and the images.mp4
036 Converting images to arrays.en.srt
036 Converting images to arrays.mp4
037 Getting started with the code concepts.en.srt
037 Getting started with the code concepts.mp4
038 Primary classification task - Part 1.en.srt
038 Primary classification task - Part 1.mp4
039 Primary classification task - Part 2.en.srt
039 Primary classification task - Part 2.mp4
040 Primary classification task - Part 3.en.srt
040 Primary classification task - Part 3.mp4
041 Trousers and Jeans - discussion of approaches.en.srt
041 Trousers and Jeans - discussion of approaches.mp4
042 Trousers and Jeans - All.en.srt
042 Trousers and Jeans - All.mp4
043 Trousers and Jeans - Gender + Type.en.srt
043 Trousers and Jeans - Gender + Type.mp4
044 Trousers and Jeans - comparing the methods.en.srt
044 Trousers and Jeans - comparing the methods.mp4
045 L2 regularization and Dropout.en.srt
045 L2 regularization and Dropout.mp4
046 Data augmentation - Shoes All.en.srt
046 Data augmentation - Shoes All.mp4
external-assets-links.txt
10 Understanding CNNs
047 Unexpected failures.en.srt
047 Unexpected failures.mp4
11 Popular CNN architectures
048 Introduction - the ILSVRC challenge.en.srt
048 Introduction - the ILSVRC challenge.mp4
049 AlexNet - CNN success.en.srt
049 AlexNet - CNN success.mp4
050 VGG - more layers.en.srt
050 VGG - more layers.mp4
051 GoogleNet - computational efficiency.en.srt
051 GoogleNet - computational efficiency.mp4
052 ResNet - revolution of depth.en.srt
052 ResNet - revolution of depth.mp4
TutsNode.com.txt
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