Modern Deep Learning in Python 12 Modern Regularization Techniques Dropout Regularization vtt

Modern Deep Learning in Python
Modern Deep Learning in Python 12 Modern Regularization Techniques Dropout Regularization vtt

Name	Modern Deep Learning in Python	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	1.6 GB
Total Files	168
Hash	61934B48E1399570BC021ACBE22E7EC3A0448953

/Modern Deep Learning in Python/12. Modern Regularization Techniques/2. Dropout Regularization.vtt	13.0 KB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/2. Dropout Regularization.mp4	23.8 MB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/3. Dropout Intuition.vtt	4.1 KB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/3. Dropout Intuition.mp4	6.4 MB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/4. Noise Injection.vtt	6.3 KB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/4. Noise Injection.mp4	9.1 MB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.vtt	2.4 KB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/5. Modern Regularization Techniques Section Summary.mp4	4.1 MB
/Modern Deep Learning in Python/6. Weight Initialization/3. Weight Initialization.vtt	9.3 KB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.vtt	2.7 KB
/Modern Deep Learning in Python/4. Momentum and adaptive learning rates/6. Adam Optimization.vtt	12.2 KB
/Modern Deep Learning in Python/6. Weight Initialization/3. Weight Initialization.mp4	14.3 MB
/Modern Deep Learning in Python/12. Modern Regularization Techniques/1. Modern Regularization Techniques Section Introduction.mp4	4.5 MB
/Modern Deep Learning in Python/13. Batch Normalization/8. Noise Perspective.vtt	2.3 KB
/Modern Deep Learning in Python/4. Momentum and adaptive learning rates/6. Adam Optimization.mp4	20.3 MB
Showing first 15 files of 168 total files