Deep Learning Patterns And Practices
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13:53:11
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00001 Part 1. Deep learning fundamentals.mp4
01:02
00002 Chapter 1 Designing modern machine learning.mp4
12:43
00003 Chapter 1 The evolution in machine learning approaches.mp4
07:41
00004 Chapter 1 Next steps in computer learning - Part 1.mp4
09:57
00005 Chapter 1 Next steps in computer learning - Part 2.mp4
08:21
00006 Chapter 1 The benefits of design patterns.mp4
06:48
00007 Chapter 2 Deep neural networks.mp4
11:11
00008 Chapter 2 Sequential API method.mp4
08:22
00009 Chapter 2 Activation functions.mp4
12:15
00010 Chapter 2 DNN binary classifier.mp4
12:39
00011 Chapter 2 Simple image classifier.mp4
11:07
00012 Chapter 3 Convolutional and residual neural networks.mp4
08:21
00013 Chapter 3 Feature detection.mp4
07:38
00014 Chapter 3 The ConvNet design for a CNN.mp4
09:34
00015 Chapter 3 VGG networks.mp4
06:45
00016 Chapter 3 Architecture.mp4
09:41
00017 Chapter 3 Batch normalization.mp4
06:23
00018 Chapter 4 Training fundamentals.mp4
08:28
00019 Chapter 4 Dataset splitting.mp4
08:07
00020 Chapter 4 Data normalization.mp4
06:09
00021 Chapter 4 Validation and overfitting.mp4
08:15
00022 Chapter 4 Convergence.mp4
10:16
00023 Chapter 4 Hyperparameters.mp4
09:07
00024 Chapter 4 Learning rate.mp4
06:27
00025 Chapter 4 Invariance.mp4
10:01
00026 Chapter 4 Scale invariance.mp4
05:51
00027 Chapter 4 Raw disk datasets.mp4
08:00
00028 Chapter 4 Resizing.mp4
06:42
00029 Part 2. Basic design pattern.mp4
02:04
00030 Chapter 5 Procedural design pattern.mp4
08:10
00031 Chapter 5 Stem component.mp4
10:02
00032 Chapter 5 ResNet.mp4
08:02
00033 Chapter 5 Pre-stem.mp4
11:31
00034 Chapter 5 Task component.mp4
11:10
00035 Chapter 5 Beyond computer vision - NLP.mp4
08:39
00036 Chapter 6 Wide convolutional neural networks.mp4
10:39
00037 Chapter 6 Inception v1 module.mp4
11:43
00038 Chapter 6 Inception v2 - Factoring convolutions.mp4
10:37
00039 Chapter 6 Normal convolution.mp4
07:41
00040 Chapter 6 ResNeXt - Wide residual neural networks.mp4
12:06
00041 Chapter 6 Beyond computer vision - Structured data.mp4
08:05
00042 Chapter 7 Alternative connectivity patterns.mp4
11:44
00043 Chapter 7 Dense block.mp4
06:55
00044 Chapter 7 Xception - Extreme Inception.mp4
10:09
00045 Chapter 7 Exit flow of Xception.mp4
07:23
00046 Chapter 7 SE-Net - Squeeze and excitation.mp4
07:07
00047 Chapter 8 Mobile convolutional neural networks.mp4
11:39
00048 Chapter 8 Stem.mp4
10:01
00049 Chapter 8 MobileNet v2.mp4
12:05
00050 Chapter 8 SqueezeNet.mp4
10:42
00051 Chapter 8 Classifier.mp4
09:05
00052 Chapter 8 ShuffleNet v1.mp4
08:57
00053 Chapter 8 Learner.mp4
06:16
00054 Chapter 8 Deployment.mp4
08:22
00055 Chapter 9 Autoencoders.mp4
11:23
00056 Chapter 9 Convolutional autoencoders.mp4
09:16
00057 Chapter 9 Super-resolution.mp4
12:18
00058 Chapter 9 Pretext tasks.mp4
09:04
00059 Part 3. Working with pipelines.mp4
02:18
00060 Chapter 10 Hyperparameter tuning.mp4
07:58
00061 Chapter 10 Lottery hypothesis.mp4
07:20
00062 Chapter 10 Hyperparameter search fundamentals.mp4
09:06
00063 Chapter 10 Random search.mp4
09:25
00064 Chapter 10 Learning rate scheduler.mp4
12:18
00065 Chapter 10 Regularization.mp4
09:28
00066 Chapter 11 Transfer learning.mp4
11:45
00067 Chapter 11 New classifier.mp4
10:21
00068 Chapter 11 TF Hub prebuilt models.mp4
11:17
00069 Chapter 11 Distinct tasks.mp4
12:23
00070 Chapter 12 Data distributions.mp4
11:21
00071 Chapter 12 Out of distribution.mp4
11:48
00072 Chapter 12 Training as a CNN.mp4
12:06
00073 Chapter 13 Data pipeline.mp4
05:28
00074 Chapter 13 Compressed and raw-image formats.mp4
09:14
00075 Chapter 13 HDF5 format.mp4
10:56
00076 Chapter 13 TFRecord format.mp4
11:33
00077 Chapter 13 Data feeding.mp4
09:45
00078 Chapter 13 Data preprocessing.mp4
12:28
00079 Chapter 13 Preprocessing with TF Extended.mp4
07:31
00080 Chapter 13 Data augmentation.mp4
11:25
00081 Chapter 14 Training and deployment pipeline.mp4
12:21
00082 Chapter 14 Model feeding with tf.data.Dataset.mp4
11:33
00083 Chapter 14 Model feeding with TFX.mp4
11:43
00084 Chapter 14 Training schedulers.mp4
12:53
00085 Chapter 14 Model evaluations.mp4
09:24
00086 Chapter 14 TFX evaluation.mp4
06:15
00087 Chapter 14 Serving predictions.mp4
11:45
00088 Chapter 14 TFX pipeline components for deployment.mp4
12:11
00089 Chapter 14 Evolution in production pipeline design.mp4
07:06
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Manning Publications
View courses Manning PublicationsManning Publications is an American publisher specializing in content relating to computers. Manning mainly publishes textbooks but also release videos and projects for professionals within the computing world.
- language english
- Training sessions 89
- duration 13:53:11
- Release Date 2023/11/06
