Filename | Size |
| 001.Specialization Promo/001. Welcome to AML specialization!.mp4 | 13.7 MB |
| 001.Specialization Promo/001. Welcome to AML specialization!.srt | 4.7 KB |
| 002.Course intro/002. Course intro.mp4 | 22.1 MB |
| 002.Course intro/002. Course intro.srt | 8.8 KB |
| 003.Linear model as the simplest neural network/003. Linear regression.mp4 | 35.7 MB |
| 003.Linear model as the simplest neural network/003. Linear regression.srt | 13.3 KB |
| 003.Linear model as the simplest neural network/004. Linear classification.mp4 | 42.7 MB |
| 003.Linear model as the simplest neural network/004. Linear classification.srt | 16.4 KB |
| 003.Linear model as the simplest neural network/005. Gradient descent.mp4 | 19 MB |
| 003.Linear model as the simplest neural network/005. Gradient descent.srt | 7.4 KB |
| 004.Regularization in machine learning/006. Overfitting problem and model validation.mp4 | 26.4 MB |
| 004.Regularization in machine learning/006. Overfitting problem and model validation.srt | 9.8 KB |
| 004.Regularization in machine learning/007. Model regularization.mp4 | 19.9 MB |
| 004.Regularization in machine learning/007. Model regularization.srt | 7.4 KB |
| 005.Stochastic methods for optimization/008. Stochastic gradient descent.mp4 | 21.1 MB |
| 005.Stochastic methods for optimization/008. Stochastic gradient descent.srt | 7.8 KB |
| 005.Stochastic methods for optimization/009. Gradient descent extensions.mp4 | 36.6 MB |
| 005.Stochastic methods for optimization/009. Gradient descent extensions.srt | 13.4 KB |
| 006.The simplest neural network MLP/010. Multilayer perceptron (MLP).mp4 | 44.7 MB |
| 006.The simplest neural network MLP/010. Multilayer perceptron (MLP).srt | 18.5 KB |
| 006.The simplest neural network MLP/011. Chain rule.mp4 | 26.6 MB |
| 006.The simplest neural network MLP/011. Chain rule.srt | 10 KB |
| 006.The simplest neural network MLP/012. Backpropagation.mp4 | 31.6 MB |
| 006.The simplest neural network MLP/012. Backpropagation.srt | 11.4 KB |
| 007.Matrix derivatives/013. Efficient MLP implementation.mp4 | 47.1 MB |
| 007.Matrix derivatives/013. Efficient MLP implementation.srt | 16.6 KB |
| 007.Matrix derivatives/014. Other matrix derivatives.mp4 | 21.4 MB |
| 007.Matrix derivatives/014. Other matrix derivatives.srt | 8.6 KB |
| 008.TensorFlow framework/015. What is TensorFlow.mp4 | 39.4 MB |
| 008.TensorFlow framework/015. What is TensorFlow.srt | 14.7 KB |
| 008.TensorFlow framework/016. Our first model in TensorFlow.mp4 | 36.8 MB |
| 008.TensorFlow framework/016. Our first model in TensorFlow.srt | 13.8 KB |
| 009.Philosophy of deep learning/017. What Deep Learning is and is not.mp4 | 29.5 MB |
| 009.Philosophy of deep learning/017. What Deep Learning is and is not.srt | 13.9 KB |
| 009.Philosophy of deep learning/018. Deep learning as a language.mp4 | 24.6 MB |
| 009.Philosophy of deep learning/018. Deep learning as a language.srt | 11.9 KB |
| 010.Introduction to CNN/019. Motivation for convolutional layers.mp4 | 41.4 MB |
| 010.Introduction to CNN/019. Motivation for convolutional layers.srt | 16 KB |
| 010.Introduction to CNN/020. Our first CNN architecture.mp4 | 42.6 MB |
| 010.Introduction to CNN/020. Our first CNN architecture.srt | 13.3 KB |
| 011.Modern CNNs/021. Training tips and tricks for deep CNNs.mp4 | 57.9 MB |
| 011.Modern CNNs/021. Training tips and tricks for deep CNNs.srt | 18.2 KB |
| 011.Modern CNNs/022. Overview of modern CNN architectures.mp4 | 32.2 MB |
| 011.Modern CNNs/022. Overview of modern CNN architectures.srt | 9.5 KB |
| 012.Applications of CNNs/023. Learning new tasks with pre-trained CNNs.mp4 | 19.3 MB |
| 012.Applications of CNNs/023. Learning new tasks with pre-trained CNNs.srt | 6.8 KB |
| 012.Applications of CNNs/024. A glimpse of other Computer Vision tasks.mp4 | 30.7 MB |
| 012.Applications of CNNs/024. A glimpse of other Computer Vision tasks.srt | 10.8 KB |
| 013.Intro to Unsupervised Learning/025. Unsupervised learning what it is and why bother.mp4 | 23.8 MB |
| 013.Intro to Unsupervised Learning/025. Unsupervised learning what it is and why bother.srt | 9.5 KB |
| 013.Intro to Unsupervised Learning/026. Autoencoders 101.mp4 | 22.1 MB |
| 013.Intro to Unsupervised Learning/026. Autoencoders 101.srt | 8.1 KB |
| 014.More Autoencoders/027. Autoencoder applications.mp4 | 40.8 MB |
| 014.More Autoencoders/027. Autoencoder applications.srt | 14.7 KB |
| 014.More Autoencoders/028. Autoencoder applications image generation, data visualization & more.mp4 | 28.2 MB |
| 014.More Autoencoders/028. Autoencoder applications image generation, data visualization & more.srt | 10.6 KB |
| 015.Word Embeddings/029. Natural language processing primer.mp4 | 36.7 MB |
| 015.Word Embeddings/029. Natural language processing primer.srt | 15.3 KB |
| 015.Word Embeddings/030. Word embeddings.mp4 | 48.3 MB |
| 015.Word Embeddings/030. Word embeddings.srt | 20.2 KB |
| 016.Generative Adversarial Networks/031. Generative models 101.mp4 | 26.7 MB |
| 016.Generative Adversarial Networks/031. Generative models 101.srt | 11.2 KB |
| 016.Generative Adversarial Networks/032. Generative Adversarial Networks.mp4 | 36.2 MB |
| 016.Generative Adversarial Networks/032. Generative Adversarial Networks.srt | 15.3 KB |
| 016.Generative Adversarial Networks/033. Applications of adversarial approach.mp4 | 41.9 MB |
| 016.Generative Adversarial Networks/033. Applications of adversarial approach.srt | 15.9 KB |
| 017.Introduction to RNN/034. Motivation for recurrent layers.mp4 | 30.2 MB |
| 017.Introduction to RNN/034. Motivation for recurrent layers.srt | 10.6 KB |
| 017.Introduction to RNN/035. Simple RNN and Backpropagation.mp4 | 35.1 MB |
| 017.Introduction to RNN/035. Simple RNN and Backpropagation.srt | 12.5 KB |
| 018.Modern RNNs/036. The training of RNNs is not that easy.mp4 | 26.4 MB |
| 018.Modern RNNs/036. The training of RNNs is not that easy.srt | 10.4 KB |
| 018.Modern RNNs/037. Dealing with vanishing and exploding gradients.mp4 | 34.9 MB |
| 018.Modern RNNs/037. Dealing with vanishing and exploding gradients.srt | 13.7 KB |
| 018.Modern RNNs/038. Modern RNNs LSTM and GRU.mp4 | 47.7 MB |
| 018.Modern RNNs/038. Modern RNNs LSTM and GRU.srt | 17.2 KB |
| 019.Applications of RNNs/039. Practical use cases for RNNs.mp4 | 56.1 MB |
| 019.Applications of RNNs/039. Practical use cases for RNNs.srt | 19.5 KB |