zhongziso种子搜
首页
功能
磁力转BT
BT转磁力
使用教程
免责声明
关于
zhongziso
搜索
[GigaCourse.com] Udemy - CNN for Computer Vision with Keras and TensorFlow in R
magnet:?xt=urn:btih:b9e318e35b8ad3985af101d3f9ea9fa132c48a43&dn=[GigaCourse.com] Udemy - CNN for Computer Vision with Keras and TensorFlow in R
磁力链接详情
Hash值:
b9e318e35b8ad3985af101d3f9ea9fa132c48a43
点击数:
228
文件大小:
2.66 GB
文件数量:
50
创建日期:
2022-3-26 14:13
最后访问:
2024-6-10 01:00
访问标签:
GigaCourse
com
Udemy
-
CNN
for
Computer
Vision
with
Keras
and
TensorFlow
in
R
文件列表详情
1. Introduction/1. Introduction.mp4 21.64 MB
10. The NeuralNets Package/1. ANN with NeuralNets Package.mp4 84.44 MB
11. Saving and Restoring Models/1. Saving - Restoring Models and Using Callbacks.mp4 216.19 MB
12. Hyperparameter Tuning/1. Hyperparameter Tuning.mp4 60.61 MB
13. CNN - Basics/1. CNN Introduction.mp4 51.17 MB
13. CNN - Basics/2. Stride.mp4 16.57 MB
13. CNN - Basics/3. Padding.mp4 31.62 MB
13. CNN - Basics/4. Filters and Feature maps.mp4 52.74 MB
13. CNN - Basics/5. Channels.mp4 67.76 MB
13. CNN - Basics/6. PoolingLayer.mp4 46.88 MB
14. Creating CNN model in R/1. CNN on MNIST Fashion Dataset - Model Architecture.mp4 7.36 MB
14. Creating CNN model in R/2. Data Preprocessing.mp4 67.01 MB
14. Creating CNN model in R/3. Creating Model Architecture.mp4 71.57 MB
14. Creating CNN model in R/4. Compiling and training.mp4 32.23 MB
14. Creating CNN model in R/5. Model Performance.mp4 68.11 MB
15. Analyzing impact of Pooling layer/1. Comparison - Pooling vs Without Pooling in R.mp4 44.56 MB
16. Project Creating CNN model from scratch/1. Project - Introduction.mp4 49.41 MB
16. Project Creating CNN model from scratch/3. Project in R - Data Preprocessing.mp4 87.73 MB
16. Project Creating CNN model from scratch/4. CNN Project in R - Structure and Compile.mp4 46.11 MB
16. Project Creating CNN model from scratch/5. Project in R - Training.mp4 24.61 MB
16. Project Creating CNN model from scratch/6. Project in R - Model Performance.mp4 23.15 MB
17. Project Data Augmentation for avoiding overfitting/1. Project in R - Data Augmentation.mp4 56.37 MB
17. Project Data Augmentation for avoiding overfitting/2. Project in R - Validation Performance.mp4 23.72 MB
18. Transfer Learning Basics/1. ILSVRC.mp4 20.95 MB
18. Transfer Learning Basics/2. LeNET.mp4 7.01 MB
18. Transfer Learning Basics/3. VGG16NET.mp4 10.36 MB
18. Transfer Learning Basics/4. GoogLeNet.mp4 21.37 MB
18. Transfer Learning Basics/5. Transfer Learning.mp4 30 MB
19. Transfer Learning in R/1. Project - Transfer Learning - VGG16 (Implementation).mp4 101.57 MB
19. Transfer Learning in R/2. Project - Transfer Learning - VGG16 (Performance).mp4 64.14 MB
2. Setting Up R Studio and R crash course/1. Installing R and R studio.mp4 35.69 MB
2. Setting Up R Studio and R crash course/2. Basics of R and R studio.mp4 38.84 MB
2. Setting Up R Studio and R crash course/3. Packages in R.mp4 82.92 MB
2. Setting Up R Studio and R crash course/4. Inputting data part 1 Inbuilt datasets of R.mp4 40.74 MB
2. Setting Up R Studio and R crash course/5. Inputting data part 2 Manual data entry.mp4 25.5 MB
2. Setting Up R Studio and R crash course/6. Inputting data part 3 Importing from CSV or Text files.mp4 60.1 MB
2. Setting Up R Studio and R crash course/7. Creating Barplots in R.mp4 96.72 MB
2. Setting Up R Studio and R crash course/8. Creating Histograms in R.mp4 42 MB
3. Single Cells - Perceptron and Sigmoid Neuron/1. Perceptron.mp4 44.76 MB
3. Single Cells - Perceptron and Sigmoid Neuron/2. Activation Functions.mp4 34.61 MB
4. Neural Networks - Stacking cells to create network/1. Basic Terminologies.mp4 40.44 MB
4. Neural Networks - Stacking cells to create network/2. Gradient Descent.mp4 60.34 MB
4. Neural Networks - Stacking cells to create network/3. Back Propagation.mp4 122.19 MB
5. Important concepts Common Interview questions/1. Some Important Concepts.mp4 62.2 MB
6. Standard Model Parameters/1. Hyperparameters.mp4 45.35 MB
7. Tensorflow and Keras/1. Keras and Tensorflow.mp4 14.93 MB
7. Tensorflow and Keras/2. Installing Keras and Tensorflow.mp4 22.81 MB
8. R - Dataset for classification problem/1. Data Normalization and Test-Train Split.mp4 111.78 MB
9. R - Building and training the Model/1. Building, Compiling and Training.mp4 130.71 MB
9. R - Building and training the Model/2. Evaluating and Predicting.mp4 99.22 MB
其他位置