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[GigaCourse.com] Udemy - CNN for Computer Vision with Keras and TensorFlow in R
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[GigaCourse.com] Udemy - CNN for Computer Vision with Keras and TensorFlow in R
磁力链接/BT种子简介
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b9e318e35b8ad3985af101d3f9ea9fa132c48a43
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收录时间:
2021-03-08
最近下载:
2025-03-13
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文件列表
11. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4
226.7 MB
9. R - Building and training the Model/1. Building, Compiling and Training.mp4
137.1 MB
4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4
128.1 MB
8. R - Dataset for classification problem/1. Data Normalization and Test-Train Split.mp4
117.2 MB
19. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4
106.5 MB
9. R - Building and training the Model/2. Evaluating and Predicting.mp4
104.0 MB
2. Setting Up R Studio and R crash course/7. Creating Barplots in R.mp4
101.4 MB
16. Project Creating CNN model from scratch/3. Project in R - Data Preprocessing.mp4
92.0 MB
10. The NeuralNets Package/1. ANN with NeuralNets Package.mp4
88.5 MB
2. Setting Up R Studio and R crash course/3. Packages in R.mp4
87.0 MB
14. Creating CNN model in R/3. Creating Model Architecture.mp4
75.1 MB
14. Creating CNN model in R/5. Model Performance.mp4
71.4 MB
13. CNN - Basics/5. Channels.mp4
71.1 MB
14. Creating CNN model in R/2. Data Preprocessing.mp4
70.3 MB
19. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).mp4
67.3 MB
5. Important concepts Common Interview questions/1. Some Important Concepts.mp4
65.2 MB
12. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4
63.6 MB
4. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4
63.3 MB
2. Setting Up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.mp4
63.0 MB
17. Project Data Augmentation for avoiding overfitting/1. Project in R - Data Augmentation.mp4
59.1 MB
13. CNN - Basics/4. Filters and Feature maps.mp4
55.3 MB
13. CNN - Basics/1. CNN Introduction.mp4
53.7 MB
16. Project Creating CNN model from scratch/1. Project - Introduction.mp4
51.8 MB
13. CNN - Basics/6. PoolingLayer.mp4
49.2 MB
16. Project Creating CNN model from scratch/4. CNN Project in R - Structure and Compile.mp4
48.3 MB
6. Standard Model Parameters/1. Hyperparameters.mp4
47.6 MB
3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4
46.9 MB
15. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in R.mp4
46.7 MB
2. Setting Up R Studio and R crash course/8. Creating Histograms in R.mp4
44.0 MB
2. Setting Up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.mp4
42.7 MB
4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4
42.4 MB
2. Setting Up R Studio and R crash course/2. Basics of R and R studio.mp4
40.7 MB
2. Setting Up R Studio and R crash course/1. Installing R and R studio.mp4
37.4 MB
3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4
36.3 MB
14. Creating CNN model in R/4. Compiling and training.mp4
33.8 MB
13. CNN - Basics/3. Padding.mp4
33.2 MB
18. Transfer Learning Basics/5. Transfer Learning.mp4
31.5 MB
2. Setting Up R Studio and R crash course/5. Inputting data part 2 Manual data entry.mp4
26.7 MB
16. Project Creating CNN model from scratch/5. Project in R - Training.mp4
25.8 MB
17. Project Data Augmentation for avoiding overfitting/2. Project in R - Validation Performance.mp4
24.9 MB
16. Project Creating CNN model from scratch/6. Project in R - Model Performance.mp4
24.3 MB
7. Tensorflow and Keras/2. Installing Keras and Tensorflow.mp4
23.9 MB
1. Introduction/1. Introduction.mp4
22.7 MB
18. Transfer Learning Basics/4. GoogLeNet.mp4
22.4 MB
18. Transfer Learning Basics/1. ILSVRC.mp4
22.0 MB
13. CNN - Basics/2. Stride.mp4
17.4 MB
7. Tensorflow and Keras/1. Keras and Tensorflow.mp4
15.7 MB
2. Setting Up R Studio and R crash course/3. Packages in R.srt
15.2 MB
18. Transfer Learning Basics/3. VGG16NET.mp4
10.9 MB
1. Introduction/2.1 ST Academy - CNN course files R.zip
7.9 MB
14. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.mp4
7.7 MB
18. Transfer Learning Basics/2. LeNET.mp4
7.3 MB
4. Neural Networks - Stacking cells to create network/3. Back Propagation.srt
23.3 kB
11. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.srt
20.9 kB
9. R - Building and training the Model/1. Building, Compiling and Training.srt
15.8 kB
2. Setting Up R Studio and R crash course/7. Creating Barplots in R.srt
13.7 kB
19. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).srt
13.4 kB
5. Important concepts Common Interview questions/1. Some Important Concepts.srt
13.4 kB
8. R - Dataset for classification problem/1. Data Normalization and Test-Train Split.srt
12.4 kB
4. Neural Networks - Stacking cells to create network/2. Gradient Descent.srt
12.2 kB
16. Project Creating CNN model from scratch/3. Project in R - Data Preprocessing.srt
11.6 kB
2. Setting Up R Studio and R crash course/2. Basics of R and R studio.srt
11.1 kB
3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.srt
9.9 kB
4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.srt
9.7 kB
12. Hyperparameter Tuning/1. Hyperparameter Tuning.srt
9.7 kB
9. R - Building and training the Model/2. Evaluating and Predicting.srt
9.7 kB
6. Standard Model Parameters/1. Hyperparameters.srt
9.2 kB
19. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).srt
8.6 kB
3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.srt
8.0 kB
10. The NeuralNets Package/1. ANN with NeuralNets Package.srt
7.9 kB
17. Project Data Augmentation for avoiding overfitting/1. Project in R - Data Augmentation.srt
7.7 kB
14. Creating CNN model in R/2. Data Preprocessing.srt
7.4 kB
16. Project Creating CNN model from scratch/1. Project - Introduction.srt
7.3 kB
13. CNN - Basics/4. Filters and Feature maps.srt
6.7 kB
2. Setting Up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.srt
6.5 kB
14. Creating CNN model in R/5. Model Performance.srt
6.4 kB
14. Creating CNN model in R/3. Creating Model Architecture.srt
6.3 kB
2. Setting Up R Studio and R crash course/8. Creating Histograms in R.srt
6.0 kB
13. CNN - Basics/5. Channels.srt
6.0 kB
2. Setting Up R Studio and R crash course/1. Installing R and R studio.srt
5.8 kB
18. Transfer Learning Basics/5. Transfer Learning.srt
5.5 kB
16. Project Creating CNN model from scratch/4. CNN Project in R - Structure and Compile.srt
5.3 kB
13. CNN - Basics/6. PoolingLayer.srt
5.2 kB
13. CNN - Basics/3. Padding.srt
4.7 kB
18. Transfer Learning Basics/1. ILSVRC.srt
4.5 kB
15. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in R.srt
4.2 kB
2. Setting Up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.srt
4.1 kB
1. Introduction/1. Introduction.srt
3.7 kB
7. Tensorflow and Keras/1. Keras and Tensorflow.srt
3.6 kB
14. Creating CNN model in R/4. Compiling and training.srt
3.1 kB
18. Transfer Learning Basics/4. GoogLeNet.srt
3.1 kB
7. Tensorflow and Keras/2. Installing Keras and Tensorflow.srt
3.0 kB
2. Setting Up R Studio and R crash course/5. Inputting data part 2 Manual data entry.srt
3.0 kB
16. Project Creating CNN model from scratch/5. Project in R - Training.srt
2.9 kB
13. CNN - Basics/2. Stride.srt
2.8 kB
17. Project Data Augmentation for avoiding overfitting/2. Project in R - Validation Performance.srt
2.6 kB
16. Project Creating CNN model from scratch/6. Project in R - Model Performance.srt
2.6 kB
18. Transfer Learning Basics/3. VGG16NET.srt
1.9 kB
18. Transfer Learning Basics/2. LeNET.srt
1.7 kB
Readme.txt
962 Bytes
16. Project Creating CNN model from scratch/2. Data for the project.html
232 Bytes
4. Neural Networks - Stacking cells to create network/4. Quiz.html
165 Bytes
5. Important concepts Common Interview questions/2. Quiz.html
165 Bytes
16. Project Creating CNN model from scratch/2.1 Download the project dataset.html
127 Bytes
1. Introduction/2. Course resources.html
82 Bytes
[GigaCourse.com].url
49 Bytes
14. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.srt
0 Bytes
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