| Episode |
Neural Networks and Deep Learning Vectorization |
1970 |
| Episode |
Neural Networks and Deep Learning More Vectorization Examples |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorizing Logistic Regression |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorizing Logistic Regression's Gradient Output |
1970 |
| Episode |
Neural Networks and Deep Learning Broadcasting in Python |
1970 |
| Episode |
Neural Networks and Deep Learning A note on python numpy vectors |
1970 |
| Episode |
Neural Networks and Deep Learning Quick tour of Jupyter iPython Notebooks |
1970 |
| Episode |
Neural Networks and Deep Learning Explanation of logistic regression cost function - optional |
1970 |
| Episode |
Neural Networks and Deep Learning Pieter Abbeel interview |
1970 |
| Episode |
Neural Networks and Deep Learning Neural Networks Overview |
1970 |
| Episode |
Neural Networks and Deep Learning Neural Network Representation |
1970 |
| Episode |
Neural Networks and Deep Learning Computing a Neural Network's Output |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorizing across multiple examples |
1970 |
| Episode |
Neural Networks and Deep Learning Explanation for Vectorized Implementation |
1970 |
| Episode |
Neural Networks and Deep Learning Activation functions |
1970 |
| Episode |
Neural Networks and Deep Learning Why do you need non-linear activation functions? |
1970 |
| Episode |
Neural Networks and Deep Learning Derivatives of activation functions |
1970 |
| Episode |
Neural Networks and Deep Learning Gradient descent for Neural Networks |
1970 |
| Episode |
Neural Networks and Deep Learning Backpropagation intuition - optional |
1970 |
| Episode |
Neural Networks and Deep Learning Random Initialization |
1970 |
| Episode |
Neural Networks and Deep Learning Ian Goodfellow interview |
1970 |
| Episode |
Neural Networks and Deep Learning Deep L-layer neural network |
1970 |
| Episode |
Neural Networks and Deep Learning Forward Propagation in a Deep Network |
1970 |
| Episode |
Neural Networks and Deep Learning Welcome |
1970 |
| Episode |
Neural Networks and Deep Learning Getting your matrix dimensions right |
1970 |
| Episode |
Neural Networks and Deep Learning Why deep representations? |
1970 |
| Episode |
Neural Networks and Deep Learning What is a neural network? |
1970 |
| Episode |
Neural Networks and Deep Learning Building blocks of deep neural networks |
1970 |
| Episode |
Neural Networks and Deep Learning Supervised Learning with Neural Networks |
1970 |
| Episode |
Neural Networks and Deep Learning About this Course |
1970 |
| Episode |
Neural Networks and Deep Learning Forward and Backward Propagation |
1970 |
| Episode |
Neural Networks and Deep Learning Course Resources |
1970 |
| Episode |
Neural Networks and Deep Learning Parameters vs Hyperparameters |
1970 |
| Episode |
Neural Networks and Deep Learning Geoffrey Hinton interview |
1970 |
| Episode |
Neural Networks and Deep Learning What does this have to do with the brain? |
1970 |
| Episode |
Neural Networks and Deep Learning Binary Classification |
1970 |
| Episode |
Neural Networks and Deep Learning Logistic Regression |
1970 |
| Episode |
Neural Networks and Deep Learning Logistic Regression Cost Function |
1970 |
| Episode |
Neural Networks and Deep Learning Gradient Descent |
1970 |
| Episode |
Neural Networks and Deep Learning Derivatives |
1970 |
| Episode |
Neural Networks and Deep Learning More Derivative Examples |
1970 |
| Episode |
Neural Networks and Deep Learning Computation graph |
1970 |
| Episode |
Neural Networks and Deep Learning Derivatives with a Computation Graph |
1970 |
| Episode |
Neural Networks and Deep Learning Logistic Regression Gradient Descent |
1970 |
| Episode |
Neural Networks and Deep Learning Gradient Descent on m Examples |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorization |
1970 |
| Episode |
Neural Networks and Deep Learning More Vectorization Examples |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorizing Logistic Regression |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorizing Logistic Regression's Gradient Output |
1970 |
| Episode |
Neural Networks and Deep Learning Broadcasting in Python |
1970 |
| Episode |
Neural Networks and Deep Learning A note on python numpy vectors |
1970 |
| Episode |
Neural Networks and Deep Learning Quick tour of Jupyter iPython Notebooks |
1970 |
| Episode |
Neural Networks and Deep Learning Explanation of logistic regression cost function - optional |
1970 |
| Episode |
Neural Networks and Deep Learning Pieter Abbeel interview |
1970 |
| Episode |
Neural Networks and Deep Learning Neural Networks Overview |
1970 |
| Episode |
Neural Networks and Deep Learning Neural Network Representation |
1970 |
| Episode |
Neural Networks and Deep Learning Computing a Neural Network's Output |
1970 |
| Episode |
Neural Networks and Deep Learning Vectorizing across multiple examples |
1970 |
| Episode |
Neural Networks and Deep Learning Explanation for Vectorized Implementation |
1970 |
| Episode |
Neural Networks and Deep Learning Activation functions |
1970 |
| Episode |
Neural Networks and Deep Learning Why do you need non-linear activation functions? |
1970 |
| Episode |
Neural Networks and Deep Learning Derivatives of activation functions |
1970 |
| Episode |
Neural Networks and Deep Learning Gradient descent for Neural Networks |
1970 |
| Episode |
Neural Networks and Deep Learning Backpropagation intuition - optional |
1970 |
| Episode |
Neural Networks and Deep Learning Random Initialization |
1970 |
| Episode |
Neural Networks and Deep Learning Ian Goodfellow interview |
1970 |
| Episode |
Neural Networks and Deep Learning Deep L-layer neural network |
1970 |
| Episode |
Neural Networks and Deep Learning Forward Propagation in a Deep Network |
1970 |
| Episode |
Neural Networks and Deep Learning Welcome |
1970 |
| Episode |
Neural Networks and Deep Learning Getting your matrix dimensions right |
1970 |
| Episode |
Neural Networks and Deep Learning Why deep representations? |
1970 |
| Episode |
Neural Networks and Deep Learning What is a neural network? |
1970 |
| Episode |
Neural Networks and Deep Learning Building blocks of deep neural networks |
1970 |
| Episode |
Neural Networks and Deep Learning Supervised Learning with Neural Networks |
1970 |
| Episode |
Neural Networks and Deep Learning Forward and Backward Propagation |
1970 |
| Episode |
Neural Networks and Deep Learning About this Course |
1970 |
| Episode |
Neural Networks and Deep Learning Course Resources |
1970 |
| Episode |
Neural Networks and Deep Learning Parameters vs Hyperparameters |
1970 |
| Episode |
Neural Networks and Deep Learning Geoffrey Hinton interview |
1970 |
| Episode |
Neural Networks and Deep Learning What does this have to do with the brain? |
1970 |
| Episode |
Neural Networks and Deep Learning Binary Classification |
1970 |
| Episode |
Neural Networks and Deep Learning Logistic Regression |
1970 |
| Episode |
Neural Networks and Deep Learning Logistic Regression Cost Function |
1970 |
| Episode |
Neural Networks and Deep Learning Gradient Descent |
1970 |
| Episode |
Neural Networks and Deep Learning Derivatives |
1970 |
| Episode |
Neural Networks and Deep Learning More Derivative Examples |
1970 |
| Episode |
Neural Networks and Deep Learning Computation graph |
1970 |
| Episode |
Neural Networks and Deep Learning Derivatives with a Computation Graph |
1970 |
| Episode |
Neural Networks and Deep Learning Logistic Regression Gradient Descent |
1970 |
| Episode |
Neural Networks and Deep Learning Gradient Descent on m Examples |
1970 |
| Episode |
Neural Networks and Deep Learning Welcome |
1970 |
