📄 1. Intro_alle_CNN_.pdf(1,18MB)
📄 1. Introduzione alle Reti Neurali Artificiali Convolutive - 6:45.mp4(16,80MB)
📄 1. Introduzione alle Reti Neurali Artificiali Convolutive - 6:45.pdf(114,46KB)
📄 2. Generalità sulla Convoluzione - 7:06.mp4(17,20MB)
📄 2. Intro_alle_CNN_.pdf(1,18MB)
📄 3. Esempio di Filtraggio - 10:06.mp4(34,85MB)
📄 3. Esempio di Filtraggio - 10:06.pdf(114,21KB)
📄 3. Intro_alle_CNN_.pdf(1,18MB)
📄 4. Il Padding - 6:25.mp4(12,63MB)
📄 4. Il Padding - 6:25.pdf(114,27KB)
📄 4. Intro_alle_CNN_.pdf(1,18MB)
📄 5. Intro_alle_CNN_.pdf(1,18MB)
📄 5. Lo Stride - 2:34.mp4(5,43MB)
📄 5. Lo Stride - 2:34.pdf(114,26KB)
📄 6. Convoluzione Volumetrica - 6:58.mp4(16,04MB)
📄 6. Convoluzione Volumetrica - 6:58.pdf(113,95KB)
📄 6. Intro_alle_CNN_.pdf(1,18MB)
📄 7. 4.02_CNN_in_Machine_Learning_.pdf(839,59KB)
📄 7. Filtri, Kernel e Parametri - 14:18.mp4(35,80MB)
📄 7. Filtri, Kernel e Parametri - 14:18.pdf(114,57KB)
📄 8. CNN_in_Machine_Learning_.pdf(839,59KB)
📄 8. Local Perceptive Fields - 10:58.mp4(23,24MB)
📄 8. Local Perceptive Fields - 10:58.pdf(114,08KB)
📄 9. CNN_in_Machine_Learning_.pdf(839,59KB)
📄 9. Weights Sharing -4:57.mp4(10,45MB)
📄 9. Weights Sharing -4:57.pdf(114,29KB)
📄 10. CNN_in_Machine_Learning_.pdf(839,59KB)
📄 10. Downsampling e Upsampling - 8:14.mp4(18,00MB)
📄 10. Downsampling e Upsampling - 8:14.pdf(114,29KB)
📄 11. Addestramento di una rete neurale convolutiva - 9:12.mp4(18,87MB)
📄 11. Addestramento di una rete neurale convolutiva - 9:12.pdf(114,45KB)
📄 11. CNN_in_Machine_Learning_.pdf(839,59KB)
📄 12. Esercitazione CNN e Keras - 23:14.mp4(78,34MB)
📄 12. Esercitazione CNN e Keras - 23:14.pdf(114,34KB)
📄 12. Jupyter.zip(37,43KB)
📄 13. Es02_LeNet_5_PYTORCH.ipynb.zip(30,61KB)
📄 13. Esercitazione LeNet-5 in Keras - 18:00.mp4(56,97MB)
📄 13. Esercitazione LeNet-5 in Keras - 18:00.pdf(114,45KB)
📄 13. Jupyter.zip(34,44KB)
📄 13. LeNet-5_.pdf(558,70KB)
📄 14. [OPZIONALE] Esercitazione LeNet-5 in PyTorch - 16:11.mp4(31,47MB)
📄 14. LeNet_5_PYTORCH.zip(46,54KB)
📄 15. Esercitazione Spam Detection - 23:52.mp4(92,54MB)
📄 15. Esercitazione Spam Detection - 23:52.pdf(114,24KB)
📄 15. Jupyter.zip(263,09KB)
📄 16. Residual Networks - 26:33.mp4(60,52MB)
📄 16. Residual Networks - 26:33.pdf(113,72KB)
📄 16. Residual_Networks_.pdf(804,47KB)
📄 17. Es04_residual_networks_PYTORCH.ipynb.zip(174,71KB)
📄 17. Esercitazione Residual Networks in Keras - 13:39.mp4(44,39MB)
📄 17. Esercitazione Residual Networks in Keras - 13:39.pdf(113,95KB)
📄 17. Jupyter.zip(96,09KB)
📄 18. [OPZIONALE] Esercitazione Residual Networks in PyTorch - 22:55.mp4(42,18MB)
📄 18. residual_networks_PYTORCH.zip(196,84KB)
📄 19. 1x1 Convolution - 26:06.mp4(54,40MB)
📄 19. 1x1 Convolution - 26:06.pdf(113,75KB)
📄 19. 1x1-conv-inception_.pdf(821,26KB)
📄 20. 1x1-conv-inception_.pdf(821,26KB)
📄 20. Inception Block e GoogLeNet - 11:29.mp4(23,07MB)
📄 20. Inception Block e GoogLeNet - 11:29.pdf(114,97KB)
📄 21. Esercitazione Inception - 5:41.mp4(33,44MB)
📄 21. Esercitazione Inception - 5:41.pdf(114,17KB)
📄 21. Jupyter.zip(1,96MB)
📄 22. 01_feature_extractor.zip(3,69MB)
📄 22. Feature Extractor - 19:25.mp4(71,41MB)
📄 22. Feature Extractor - 19:25.pdf(115,85KB)
📄 23. Analisi di feature maps - 11:23.mp4(54,08MB)
📄 23. Analisi di feature maps - 11:23.pdf(114,69KB)
📄 23. Archivio.zip(18,56MB)
📄 24. Archivio.zip(14,46MB)
📄 24. Generare attivazioni per una CNN - 31:39.mp4(102,86MB)
📄 24. Generare attivazioni per una CNN - 31:39.pdf(114,61KB)
📄 25. U-Net - 12:38.mp4(30,74MB)
📄 25. U-Net - 12:38.pdf(114,12KB)
📄 25. unet_.pdf(1,12MB)
📄 26. Esercitazione U-Net - 17:40.mp4(76,79MB)
📄 26. Esercitazione U-Net - 17:40.pdf(114,85KB)
📄 26. Jupyter.zip(300,91KB)
📄 27. Dropout - 8:04.mp4(19,52MB)
📄 27. Dropout - 8:04.pdf(113,91KB)
📄 27. Dropout_.pdf(604,24KB)
📄 28. Esercitazione Dropout - 12:34.mp4(41,43MB)
📄 28. Esercitazione Dropout - 12:34.pdf(114,10KB)
📄 28. Jupyter.zip(63,59KB)
📄 29. Batch Normalization - 11:30.mp4(24,42MB)
📄 29. Batch Normalization - 11:30.pdf(114,18KB)
📄 29. batch_normalization_.pdf(407,78KB)
📄 30. Esercitazione LeNet-5 con Batch Normalization - 7:47.mp4(28,30MB)
📄 30. Esercitazione LeNet-5 con Batch Normalization - 7:47.pdf(114,39KB)
📄 30. Jupyter.zip(18,03KB)
📄 31. Global Pooling - 7:01.mp4(15,19MB)
📄 31. Global Pooling - 7:01.pdf(114,50KB)
📄 31. Global_Pooling_.pdf(403,92KB)
📄 32. Esercitazione su Tensorflow Datasets - 22:25.mp4(76,53MB)
📄 32. Esercitazione su Tensorflow Datasets - 22:25.pdf(114,79KB)
📄 32. Jupyter.zip(1,29MB)
📄 33. Esercitazione Global Pooling - 17:55.mp4(73,70MB)
📄 33. Esercitazione Global Pooling - 17:55.pdf(115,01KB)
📄 33. Jupyter.zip(438,26KB)
📄 34. Autoencoder - 17:45.mp4(36,34MB)
📄 34. Autoencoder - 17:45.pdf(114,13KB)
📄 34. Autoencoder_.pdf(344,31KB)
📄 35. Esercitazione Autoencoder - 34:14.mp4(114,93MB)
📄 35. Esercitazione Autoencoder - 34:14.pdf(114,60KB)
📄 35. Jupyter.zip(36,31MB)
📄 36. GAN - 22:56.mp4(44,75MB)
📄 36. GAN - 22:56.pdf(114,78KB)
📄 36. gan_.pdf(312,70KB)
📄 37. Esercitazione GAN - 29:10.mp4(106,50MB)
📄 37. Esercitazione GAN - 29:10.pdf(114,88KB)
📄 37. Jupyter.zip(318,41KB)
📄 38. Transfer Learning - 8:57.mp4(26,36MB)
📄 38. Transfer Learning - 8:57.pdf(114,33KB)
📄 38. Transfer_Learning_.pdf(633,43KB)
📄 39. Esercitazione Transfer Learning - 21:38.mp4(79,58MB)
📄 39. Esercitazione Transfer Learning - 21:38.pdf(114,71KB)
📄 39. Jupyter.zip(931,37KB)
📄 40. VAE_.pdf(828,80KB)
📄 40. Variational AutoEncoder - Introduzione - 03:45.mp4(9,78MB)
📄 40. Variational AutoEncoder - Introduzione - 03:45.pdf(115,09KB)
📄 41. Variational AutoEncoder - Richiami su spazio latente - 03:10.mp4(7,74MB)
📄 41. Variational AutoEncoder - Richiami su spazio latente - 03:10.pdf(114,37KB)
📄 42. Variational AutoEncoder - Spazio latente di un VAE - 03:46.mp4(9,38MB)
📄 42. Variational AutoEncoder - Spazio latente di un VAE - 03:46.pdf(114,88KB)
📄 43. Variational AutoEncoder - Architettura di un VAE - 03:22.mp4(8,21MB)
📄 43. Variational AutoEncoder - Architettura di un VAE - 03:22.pdf(115,11KB)
📄 44. Variational AutoEncoder - Funzione di Costo - 02:47.mp4(6,94MB)
📄 44. Variational AutoEncoder - Funzione di Costo - 02:47.pdf(115,17KB)
📄 45. Variational AutoEncoder - Reconstruction Loss - 07:02.mp4(17,65MB)
📄 45. Variational AutoEncoder - Reconstruction Loss - 07:02.pdf(115,58KB)
📄 46. Variational AutoEncoder - KL divergence - 10:00.mp4(23,20MB)
📄 46. Variational AutoEncoder - KL divergence - 10:00.pdf(115,18KB)
📄 47. Variational AutoEncoder - Reparametrization Trick - 05:20.mp4(12,57MB)
📄 47. Variational AutoEncoder - Reparametrization Trick - 05:20.pdf(115,58KB)
📄 48. Variational AutoEncoder - Costruire un VAE su dataset MNIST - 48:27.mp4(127,94MB)
📄 48. Variational AutoEncoder - Costruire un VAE su dataset MNIST - 48:27.pdf(115,61KB)
📄 48. Variational_Auto_Encoder.ipynb.zip(8,98KB)
📄 49. Neural Style Transfer - Introduzione - 04:05.mp4(11,56MB)
📄 49. Neural Style Transfer - Introduzione - 04:05.pdf(115,34KB)
📄 49. Neural_Style_Transfer_.pdf(1,13MB)
📄 50. Neural Style Transfer - Architettura della VGG - 02:43.mp4(7,83MB)
📄 50. Neural Style Transfer - Architettura della VGG - 02:43.pdf(115,87KB)
📄 51. Neural Style Transfer - Matrici di Gram - 05:05.mp4(12,44MB)
📄 51. Neural Style Transfer - Matrici di Gram - 05:05.pdf(115,24KB)
📄 52. Neural Style Transfer - Prodotto scalare fra matrici di Gram - 02:53.mp4(7,38MB)
📄 52. Neural Style Transfer - Prodotto scalare fra matrici di Gram - 02:53.pdf(115,26KB)
📄 53. Neural Style Transfer - Funzione di costo - 03:21.mp4(8,98MB)
📄 53. Neural Style Transfer - Funzione di costo - 03:21.pdf(115,26KB)
📄 54. Neural Style Transfer - Content Loss - 02:31.mp4(6,96MB)
📄 54. Neural Style Transfer - Content Loss - 02:31.pdf(115,11KB)
📄 55. Neural Style Transfer - Style Loss - 03:57.mp4(10,09MB)
📄 55. Neural Style Transfer - Style Loss - 03:57.pdf(115,23KB)
📄 56. Neural Style Transfer - Total Variation Loss - 04:50.mp4(12,02MB)
📄 56. Neural Style Transfer - Total Variation Loss - 04:50.pdf(115,23KB)
📄 57. Neural Style Transfer - Estrazione di stile da dipinti famosi - 23:13.mp4(60,73MB)
📄 57. Neural Style Transfer - Estrazione di stile da dipinti famosi - 23:13.pdf(115,54KB)
📄 57. style_extraction.zip(13,37MB)
📄 58. Neural Style Transfer - Algoritmo completo - 15:44.mp4(69,18MB)
📄 58. Neural Style Transfer - Algoritmo completo - 15:44.pdf(115,40KB)
📄 58. nst.zip(29,23MB)