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Please note that this page does not hosts or makes available any of the listed filenames. You
cannot download any of those files from here.
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| 10 - Feature scaling.en_US.vtt |
3.40KB |
| 10 - Feature scaling.mp4 |
23.44MB |
| 11 - Building the Artificial Neural Network.en_US.vtt |
1.66KB |
| 11 - Building the Artificial Neural Network.mp4 |
15.93MB |
| 12 - Adding the input layer and the first hidden layer.en_US.vtt |
2.77KB |
| 12 - Adding the input layer and the first hidden layer.mp4 |
23.52MB |
| 13 - Adding the next hidden layer.en_US.vtt |
1.10KB |
| 13 - Adding the next hidden layer.mp4 |
11.22MB |
| 14 - Adding the output layer.en_US.vtt |
1.42KB |
| 14 - Adding the output layer.mp4 |
12.17MB |
| 15 - Compiling the artificial neural network.en_US.vtt |
2.58KB |
| 15 - Compiling the artificial neural network.mp4 |
19.63MB |
| 16 - Fitting the ANN model to the training set.en_US.vtt |
2.03KB |
| 16 - Fitting the ANN model to the training set.mp4 |
22.45MB |
| 17 - Predicting the test set results.en_US.vtt |
4.06KB |
| 17 - Predicting the test set results.mp4 |
25.94MB |
| 1 - BONUS Section - Don't Miss Out.html |
893B |
| 1 - Dataset.en_US.vtt |
850B |
| 1 - Dataset.mp4 |
6.18MB |
| 1 - Feed-forward and Back Propagation Networks.en_US.vtt |
1.11KB |
| 1 - Feed-forward and Back Propagation Networks.mp4 |
5.78MB |
| 1 - How artificial neural networks work.en_US.vtt |
3.36KB |
| 1 - How artificial neural networks work.mp4 |
23.23MB |
| 1 - Introduction.en_US.vtt |
1.27KB |
| 1 - Introduction.en_US.vtt |
575B |
| 1 - Introduction.en_US.vtt |
3.75KB |
| 1 - Introduction.mp4 |
8.90MB |
| 1 - Introduction.mp4 |
4.70MB |
| 1 - Introduction.mp4 |
20.99MB |
| 1 - Single layer perceptron (SLP) model.en_US.vtt |
1009B |
| 1 - Single layer perceptron (SLP) model.mp4 |
4.75MB |
| 1 - What is a Deep Learning.en_US.vtt |
3.39KB |
| 1 - What is a Deep Learning.mp4 |
11.64MB |
| 1 - What is Gradient Decent.en_US.vtt |
1.83KB |
| 1 - What is Gradient Decent.mp4 |
9.43MB |
| 1 - What is the Activation Function.en_US.vtt |
1.65KB |
| 1 - What is the Activation Function.mp4 |
8.60MB |
| 2 - Advantages of Neural Networks.en_US.vtt |
1.08KB |
| 2 - Advantages of Neural Networks.mp4 |
4.17MB |
| 2 - Anatomy and function of neurons.en_US.vtt |
1.29KB |
| 2 - Anatomy and function of neurons.mp4 |
7.20MB |
| 2 - Backpropagation In Neural Networks.en_US.vtt |
779B |
| 2 - Backpropagation In Neural Networks.mp4 |
5.40MB |
| 2 - Components of convolutional neural networks.en_US.vtt |
897B |
| 2 - Components of convolutional neural networks.mp4 |
5.89MB |
| 2 - Course Materials.html |
148B |
| 2 - Course Materials - ANN_Codes.ipynb |
2.73MB |
| 2 - Course Materials - Churn_Modelling.csv |
668.81KB |
| 2 - Course Materials - CNN_Codes.ipynb |
5.18KB |
| 2 - Course Materials - Course Slides.pdf |
4.31MB |
| 2 - Course Materials - mnist_test.csv |
17.46MB |
| 2 - Course Materials - mnist_train.csv |
104.56MB |
| 2 - Exploring the dataset.en_US.vtt |
1.13KB |
| 2 - Exploring the dataset.mp4 |
11.46MB |
| 2 - Important Terminologies.en_US.vtt |
674B |
| 2 - Important Terminologies.mp4 |
4.63MB |
| 2 - Importing libraries.en_US.vtt |
2.15KB |
| 2 - Importing libraries.mp4 |
11.09MB |
| 2 - Radial Basis Network (RBN).en_US.vtt |
827B |
| 2 - Radial Basis Network (RBN).mp4 |
4.39MB |
| 2 - What is Stochastic Gradient Decent.en_US.vtt |
1.75KB |
| 2 - What is Stochastic Gradient Decent.mp4 |
6.04MB |
| 3 - An introduction to the neural network.en_US.vtt |
3.07KB |
| 3 - An introduction to the neural network.mp4 |
11.54MB |
| 3 - Building the CNN model.en_US.vtt |
9.74KB |
| 3 - Building the CNN model.mp4 |
47.58MB |
| 3 - Convolution Layer.en_US.vtt |
3.23KB |
| 3 - Convolution Layer.mp4 |
11.99MB |
| 3 - Disadvantages of Neural Networks.en_US.vtt |
693B |
| 3 - Disadvantages of Neural Networks.mp4 |
3.39MB |
| 3 - Gradient Decent vs Stochastic Gradient Decent.en_US.vtt |
728B |
| 3 - Gradient Decent vs Stochastic Gradient Decent.mp4 |
6.16MB |
| 3 - Minimizing the cost function using backpropagation.en_US.vtt |
1.41KB |
| 3 - Minimizing the cost function using backpropagation.mp4 |
4.95MB |
| 3 - Multi-layer perceptron (MLP) Neural Network.en_US.vtt |
717B |
| 3 - Multi-layer perceptron (MLP) Neural Network.mp4 |
4.71MB |
| 3 - Problem Statement.en_US.vtt |
747B |
| 3 - Problem Statement.mp4 |
3.21MB |
| 3 - The sigmoid function.en_US.vtt |
2.00KB |
| 3 - The sigmoid function.mp4 |
7.07MB |
| 3 - Why is Deep Learning Important.en_US.vtt |
1.83KB |
| 3 - Why is Deep Learning Important.mp4 |
7.15MB |
| 4 - Accuracy of the model.en_US.vtt |
689B |
| 4 - Accuracy of the model.mp4 |
8.75MB |
| 4 - Applications of Neural Networks.en_US.vtt |
1.85KB |
| 4 - Applications of Neural Networks.mp4 |
6.43MB |
| 4 - Architecture of a neural network.en_US.vtt |
1.53KB |
| 4 - Architecture of a neural network.mp4 |
9.13MB |
| 4 - Data Pre-processing.en_US.vtt |
3.47KB |
| 4 - Data Pre-processing.mp4 |
13.67MB |
| 4 - Hyperbolic tangent function.en_US.vtt |
1.20KB |
| 4 - Hyperbolic tangent function.mp4 |
6.31MB |
| 4 - Pooling Layer.en_US.vtt |
1.82KB |
| 4 - Pooling Layer.mp4 |
9.69MB |
| 4 - Recurrent neural network (RNN).en_US.vtt |
1.13KB |
| 4 - Recurrent neural network (RNN).mp4 |
5.98MB |
| 4 - Software and Frameworks.en_US.vtt |
799B |
| 4 - Software and Frameworks.mp4 |
5.39MB |
| 5 - Fully connected Layer.en_US.vtt |
1.70KB |
| 5 - Fully connected Layer.mp4 |
9.38MB |
| 5 - Loading the dataset.en_US.vtt |
1.09KB |
| 5 - Loading the dataset.mp4 |
9.18MB |
| 5 - Long Short-Term Memory (LSTM) networks.en_US.vtt |
1.29KB |
| 5 - Long Short-Term Memory (LSTM) networks.mp4 |
6.55MB |
| 5 - Softmax function.en_US.vtt |
821B |
| 5 - Softmax function.mp4 |
4.20MB |
| 6 - Hopfield neural network.en_US.vtt |
1.11KB |
| 6 - Hopfield neural network.mp4 |
5.30MB |
| 6 - Rectified Linear Unit (ReLU) function.en_US.vtt |
1.35KB |
| 6 - Rectified Linear Unit (ReLU) function.mp4 |
5.29MB |
| 6 - Splitting the dataset into independent and dependent variables.en_US.vtt |
2.75KB |
| 6 - Splitting the dataset into independent and dependent variables.mp4 |
22.81MB |
| 7 - Boltzmann Machine Neural Network.en_US.vtt |
841B |
| 7 - Boltzmann Machine Neural Network.mp4 |
4.66MB |
| 7 - Label encoding using scikit-learn.en_US.vtt |
3.92KB |
| 7 - Label encoding using scikit-learn.mp4 |
28.03MB |
| 7 - Leaky Rectified Linear Unit function.en_US.vtt |
776B |
| 7 - Leaky Rectified Linear Unit function.mp4 |
3.96MB |
| 8 - One-hot encoding using scikit-learn.en_US.vtt |
5.79KB |
| 8 - One-hot encoding using scikit-learn.mp4 |
37.86MB |
| 9 - Training and Test Sets Splitting Data.en_US.vtt |
3.07KB |
| 9 - Training and Test Sets Splitting Data.mp4 |
26.45MB |
| Bonus Resources.txt |
70B |
| Get Bonus Downloads Here.url |
180B |