Udemy Python for Deep Learning Build Neural Networks in Pytho
Torrent Info
| Category | Other |
| Added | Friday 24th October 2025 02:13:53 AM (1 year ago) |
| Size | 785.3 MB |
| Peers | 6 Peers (6 Seeders and 0 leechers) update |
| Downloaded | 2544 times |
| Uploader | freecoursewb Thank You (0) Report Torrent 00/0 |
| Comments | None |
| Uploader Comments | None |
| Tags | English |
| Seeders | 6 |
| Leechers | 0 |
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| Filename | Size |
|---|---|
| Get Bonus Downloads Here.url | 180 bytes |
| 1 - What is a Deep Learning.en_US.vtt | 3.4 KB |
| 1 - What is a Deep Learning.mp4 | 11.6 MB |
| 2 - Course Materials - ANN_Codes.ipynb | 2.7 MB |
| 2 - Course Materials - CNN_Codes.ipynb | 5.2 KB |
| 2 - Course Materials - Churn_Modelling.csv | 668.8 KB |
| 2 - Course Materials - Course Slides.pdf | 4.3 MB |
| 2 - Course Materials - mnist_test.csv | 17.5 MB |
| 2 - Course Materials - mnist_train.csv | 104.6 MB |
| 2 - Course Materials.html | 148 bytes |
| 3 - Why is Deep Learning Important.en_US.vtt | 1.8 KB |
| 3 - Why is Deep Learning Important.mp4 | 7.1 MB |
| 4 - Software and Frameworks.en_US.vtt | 799 bytes |
| 4 - Software and Frameworks.mp4 | 5.4 MB |
| 1 - Dataset.en_US.vtt | 850 bytes |
| 1 - Dataset.mp4 | 6.2 MB |
| 2 - Importing libraries.en_US.vtt | 2.1 KB |
| 2 - Importing libraries.mp4 | 11.1 MB |
| 3 - Building the CNN model.en_US.vtt | 9.7 KB |
| 3 - Building the CNN model.mp4 | 47.6 MB |
| 4 - Accuracy of the model.en_US.vtt | 689 bytes |
| 4 - Accuracy of the model.mp4 | 8.8 MB |
| 1 - BONUS Section - Don't Miss Out.html | 893 bytes |
| 1 - Introduction.en_US.vtt | 1.3 KB |
| 1 - Introduction.mp4 | 8.9 MB |
| 2 - Anatomy and function of neurons.en_US.vtt | 1.3 KB |
| 2 - Anatomy and function of neurons.mp4 | 7.2 MB |
| 3 - An introduction to the neural network.en_US.vtt | 3.1 KB |
| 3 - An introduction to the neural network.mp4 | 11.5 MB |
| 4 - Architecture of a neural network.en_US.vtt | 1.5 KB |
| 4 - Architecture of a neural network.mp4 | 9.1 MB |
| 1 - Feed-forward and Back Propagation Networks.en_US.vtt | 1.1 KB |
| 1 - Feed-forward and Back Propagation Networks.mp4 | 5.8 MB |
| 2 - Backpropagation In Neural Networks.en_US.vtt | 779 bytes |
| 2 - Backpropagation In Neural Networks.mp4 | 5.4 MB |
| 3 - Minimizing the cost function using backpropagation.en_US.vtt | 1.4 KB |
| 3 - Minimizing the cost function using backpropagation.mp4 | 5.0 MB |
| 1 - Single layer perceptron (SLP) model.en_US.vtt | 1009 bytes |
| 1 - Single layer perceptron (SLP) model.mp4 | 4.7 MB |
| 2 - Radial Basis Network (RBN).en_US.vtt | 827 bytes |
| 2 - Radial Basis Network (RBN).mp4 | 4.4 MB |
| 3 - Multi-layer perceptron (MLP) Neural Network.en_US.vtt | 717 bytes |
| 3 - Multi-layer perceptron (MLP) Neural Network.mp4 | 4.7 MB |
| 4 - Recurrent neural network (RNN).en_US.vtt | 1.1 KB |
| 4 - Recurrent neural network (RNN).mp4 | 6.0 MB |
| 5 - Long Short-Term Memory (LSTM) networks.en_US.vtt | 1.3 KB |
| 5 - Long Short-Term Memory (LSTM) networks.mp4 | 6.5 MB |
| 6 - Hopfield neural network.en_US.vtt | 1.1 KB |
| 6 - Hopfield neural network.mp4 | 5.3 MB |
| 7 - Boltzmann Machine Neural Network.en_US.vtt | 841 bytes |
| 7 - Boltzmann Machine Neural Network.mp4 | 4.7 MB |
| 1 - What is the Activation Function.en_US.vtt | 1.6 KB |
| 1 - What is the Activation Function.mp4 | 8.6 MB |
| 2 - Important Terminologies.en_US.vtt | 674 bytes |
| 2 - Important Terminologies.mp4 | 4.6 MB |
| 3 - The sigmoid function.en_US.vtt | 2.0 KB |
| 3 - The sigmoid function.mp4 | 7.1 MB |
| 4 - Hyperbolic tangent function.en_US.vtt | 1.2 KB |
| 4 - Hyperbolic tangent function.mp4 | 6.3 MB |
| 5 - Softmax function.en_US.vtt | 821 bytes |
| 5 - Softmax function.mp4 | 4.2 MB |
| 6 - Rectified Linear Unit (ReLU) function.en_US.vtt | 1.4 KB |
| 6 - Rectified Linear Unit (ReLU) function.mp4 | 5.3 MB |
| 7 - Leaky Rectified Linear Unit function.en_US.vtt | 776 bytes |
| 7 - Leaky Rectified Linear Unit function.mp4 | 4.0 MB |
| 1 - What is Gradient Decent.en_US.vtt | 1.8 KB |
| 1 - What is Gradient Decent.mp4 | 9.4 MB |
| 2 - What is Stochastic Gradient Decent.en_US.vtt | 1.8 KB |
| 2 - What is Stochastic Gradient Decent.mp4 | 6.0 MB |
| 3 - Gradient Decent vs Stochastic Gradient Decent.en_US.vtt | 728 bytes |
| 3 - Gradient Decent vs Stochastic Gradient Decent.mp4 | 6.2 MB |
| 1 - How artificial neural networks work.en_US.vtt | 3.4 KB |
| 1 - How artificial neural networks work.mp4 | 23.2 MB |
| 2 - Advantages of Neural Networks.en_US.vtt | 1.1 KB |
| 2 - Advantages of Neural Networks.mp4 | 4.2 MB |
| 3 - Disadvantages of Neural Networks.en_US.vtt | 693 bytes |
| 3 - Disadvantages of Neural Networks.mp4 | 3.4 MB |
| 4 - Applications of Neural Networks.en_US.vtt | 1.8 KB |
| 4 - Applications of Neural Networks.mp4 | 6.4 MB |
| 1 - Introduction.en_US.vtt | 575 bytes |
| 1 - Introduction.mp4 | 4.7 MB |
| 10 - Feature scaling.en_US.vtt | 3.4 KB |
| 10 - Feature scaling.mp4 | 23.4 MB |
| 11 - Building the Artificial Neural Network.en_US.vtt | 1.7 KB |
| 11 - Building the Artificial Neural Network.mp4 | 15.9 MB |
| 12 - Adding the input layer and the first hidden layer.en_US.vtt | 2.8 KB |
| 12 - Adding the input layer and the first hidden layer.mp4 | 23.5 MB |
| 13 - Adding the next hidden layer.en_US.vtt | 1.1 KB |
| 13 - Adding the next hidden layer.mp4 | 11.2 MB |
| 14 - Adding the output layer.en_US.vtt | 1.4 KB |
| 14 - Adding the output layer.mp4 | 12.2 MB |
| 15 - Compiling the artificial neural network.en_US.vtt | 2.6 KB |
| 15 - Compiling the artificial neural network.mp4 | 19.6 MB |
| 16 - Fitting the ANN model to the training set.en_US.vtt | 2.0 KB |
| 16 - Fitting the ANN model to the training set.mp4 | 22.4 MB |
| 17 - Predicting the test set results.en_US.vtt | 4.1 KB |
| 17 - Predicting the test set results.mp4 | 25.9 MB |
| 2 - Exploring the dataset.en_US.vtt | 1.1 KB |
| 2 - Exploring the dataset.mp4 | 11.5 MB |
| 3 - Problem Statement.en_US.vtt | 747 bytes |
| 3 - Problem Statement.mp4 | 3.2 MB |
| 4 - Data Pre-processing.en_US.vtt | 3.5 KB |
| 4 - Data Pre-processing.mp4 | 13.7 MB |
| 5 - Loading the dataset.en_US.vtt | 1.1 KB |
| 5 - Loading the dataset.mp4 | 9.2 MB |
| 6 - Splitting the dataset into independent and dependent variables.en_US.vtt | 2.8 KB |
| 6 - Splitting the dataset into independent and dependent variables.mp4 | 22.8 MB |
| 7 - Label encoding using scikit-learn.en_US.vtt | 3.9 KB |
| 7 - Label encoding using scikit-learn.mp4 | 28.0 MB |
| 8 - One-hot encoding using scikit-learn.en_US.vtt | 5.8 KB |
| 8 - One-hot encoding using scikit-learn.mp4 | 37.9 MB |
| 9 - Training and Test Sets Splitting Data.en_US.vtt | 3.1 KB |
| 9 - Training and Test Sets Splitting Data.mp4 | 26.4 MB |
| 1 - Introduction.en_US.vtt | 3.8 KB |
| 1 - Introduction.mp4 | 21.0 MB |
| 2 - Components of convolutional neural networks.en_US.vtt | 897 bytes |
| 2 - Components of convolutional neural networks.mp4 | 5.9 MB |
| 3 - Convolution Layer.en_US.vtt | 3.2 KB |
| 3 - Convolution Layer.mp4 | 12.0 MB |
| 4 - Pooling Layer.en_US.vtt | 1.8 KB |
| 4 - Pooling Layer.mp4 | 9.7 MB |
| 5 - Fully connected Layer.en_US.vtt | 1.7 KB |
| 5 - Fully connected Layer.mp4 | 9.4 MB |
| Bonus Resources.txt | 70 bytes |
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