DevCourseWeb com Udemy Python for Deep Learning Build Neural Networks in Python

DevCourseWeb com Udemy Python for Deep Learning Build Neural Networks in Python

Name	[ DevCourseWeb.com ] Udemy - Python for Deep Learning - Build Neural Networks in Python	DOWNLOAD Copy Link
Total Size	687.9 MB
Total Files	116
Last Seen	2024-07-23 00:51
Hash	227F4034DB6A3B4C3CD90B8D5946B1B520390678

/
Get Bonus Downloads Here.url	0.2 KB
/.../1. Introduction to Deep Learning/
1. What is a Deep Learning .mp4	12.2 MB
1. What is a Deep Learning .srt	4.0 KB
2. Why is Deep Learning Important.mp4	7.5 MB
2. Why is Deep Learning Important.srt	2.1 KB
3. Software and Frameworks.mp4	5.7 MB
3. Software and Frameworks.srt	0.9 KB
/.../10. Implementation of CNN in Python/
1. Dataset.mp4	6.5 MB
1. Dataset.srt	1.0 KB
2. Importing libraries.mp4	11.6 MB
2. Importing libraries.srt	2.6 KB
3. Building the CNN model.mp4	49.9 MB
3. Building the CNN model.srt	11.7 KB
4. Accuracy of the model.mp4	9.2 MB
4. Accuracy of the model.srt	0.8 KB
/.../2. Artificial Neural Networks (ANN)/
1. Introduction.mp4	9.3 MB
1. Introduction.srt	1.5 KB
2. Anatomy and function of neurons.mp4	7.6 MB
2. Anatomy and function of neurons.srt	1.5 KB
3. An introduction to the neural network.mp4	12.1 MB
3. An introduction to the neural network.srt	3.6 KB
4. Architecture of a neural network.mp4	9.6 MB
4. Architecture of a neural network.srt	1.8 KB
/.../3. Propagation of information in ANNs/
1. Feed-forward and Back Propagation Networks.mp4	6.1 MB
1. Feed-forward and Back Propagation Networks.srt	1.2 KB
2. Backpropagation In Neural Networks.mp4	5.7 MB
2. Backpropagation In Neural Networks.srt	0.9 KB
3. Minimizing the cost function using backpropagation.mp4	5.2 MB
3. Minimizing the cost function using backpropagation.srt	1.7 KB
/.../4. Neural Network Architectures/
1. Single layer perceptron (SLP) model.mp4	5.0 MB
1. Single layer perceptron (SLP) model.srt	1.1 KB
2. Radial Basis Network (RBN).mp4	4.6 MB
2. Radial Basis Network (RBN).srt	0.9 KB
3. Multi-layer perceptron (MLP) Neural Network.mp4	4.9 MB
3. Multi-layer perceptron (MLP) Neural Network.srt	0.8 KB
4. Recurrent neural network (RNN).mp4	6.3 MB
4. Recurrent neural network (RNN).srt	1.3 KB
5. Long Short-Term Memory (LSTM) networks.mp4	6.9 MB
5. Long Short-Term Memory (LSTM) networks.srt	1.5 KB
6. Hopfield neural network.mp4	5.6 MB
6. Hopfield neural network.srt	1.3 KB
7. Boltzmann Machine Neural Network.mp4	4.9 MB
7. Boltzmann Machine Neural Network.srt	1.0 KB
/5. Activation Functions/
1. What is the Activation Function.mp4	9.0 MB
1. What is the Activation Function.srt	1.9 KB
2. Important Terminologies.mp4	4.9 MB
2. Important Terminologies.srt	0.7 KB
3. The sigmoid function.mp4	7.4 MB
3. The sigmoid function.srt	2.3 KB
4. Hyperbolic tangent function.mp4	6.6 MB
4. Hyperbolic tangent function.srt	1.4 KB
5. Softmax function.mp4	4.4 MB
5. Softmax function.srt	0.9 KB
6. Rectified Linear Unit (ReLU) function.mp4	5.6 MB
6. Rectified Linear Unit (ReLU) function.srt	1.6 KB
7. Leaky Rectified Linear Unit function.mp4	4.2 MB
7. Leaky Rectified Linear Unit function.srt	0.9 KB
/.../6. Gradient Descent Algorithm/
1. What is Gradient Decent.mp4	9.9 MB
1. What is Gradient Decent.srt	2.1 KB
2. What is Stochastic Gradient Decent.mp4	6.3 MB
2. What is Stochastic Gradient Decent.srt	2.0 KB
3. Gradient Decent vs Stochastic Gradient Decent.mp4	6.5 MB
3. Gradient Decent vs Stochastic Gradient Decent.srt	0.8 KB
/.../7. Summary Overview of Neural Networks/
1. How artificial neural networks work.mp4	24.4 MB
1. How artificial neural networks work.srt	3.9 KB
2. Advantages of Neural Networks.mp4	4.4 MB
2. Advantages of Neural Networks.srt	1.3 KB
3. Disadvantages of Neural Networks.mp4	3.6 MB
3. Disadvantages of Neural Networks.srt	0.8 KB
4. Applications of Neural Networks.mp4	6.8 MB
4. Applications of Neural Networks.srt	2.2 KB
/.../8. Implementation of ANN in Python/
1. Introduction.mp4	4.9 MB
1. Introduction.srt	0.6 KB
10. Feature scaling.mp4	24.6 MB
10. Feature scaling.srt	4.0 KB
11. Building the Artificial Neural Network.mp4	16.7 MB
11. Building the Artificial Neural Network.srt	2.0 KB
12. Adding the input layer and the first hidden layer.mp4	24.7 MB
12. Adding the input layer and the first hidden layer.srt	3.2 KB
13. Adding the next hidden layer.mp4	11.8 MB
13. Adding the next hidden layer.srt	1.3 KB
14. Adding the output layer.mp4	12.8 MB
14. Adding the output layer.srt	1.7 KB
15. Compiling the artificial neural network.mp4	20.6 MB
15. Compiling the artificial neural network.srt	3.0 KB
16. Fitting the ANN model to the training set.mp4	23.5 MB
16. Fitting the ANN model to the training set.srt	2.4 KB
17. Predicting the test set results.mp4	27.2 MB
17. Predicting the test set results.srt	4.8 KB
2. Exploring the dataset.mp4	12.0 MB
2. Exploring the dataset.srt	1.3 KB
3. Problem Statement.mp4	3.4 MB
3. Problem Statement.srt	0.8 KB
4. Data Pre-processing.mp4	14.3 MB
4. Data Pre-processing.srt	4.1 KB
5. Loading the dataset.mp4	9.6 MB
5. Loading the dataset.srt	1.2 KB
6. Splitting the dataset into independent and dependent variables.mp4	23.9 MB
6. Splitting the dataset into independent and dependent variables.srt	3.3 KB
7. Label encoding using scikit-learn.mp4	29.4 MB
7. Label encoding using scikit-learn.srt	4.6 KB
8. One-hot encoding using scikit-learn.mp4	39.7 MB
8. One-hot encoding using scikit-learn.srt	6.9 KB
9. Training and Test Sets Splitting Data.mp4	27.7 MB
9. Training and Test Sets Splitting Data.srt	3.6 KB
/.../9. Convolutional Neural Networks (CNN)/
1. Introduction.mp4	22.0 MB
1. Introduction.srt	4.3 KB
2. Components of convolutional neural networks.mp4	6.2 MB
2. Components of convolutional neural networks.srt	1.0 KB
3. Convolution Layer.mp4	12.6 MB
3. Convolution Layer.srt	3.7 KB
4. Pooling Layer.mp4	10.2 MB
4. Pooling Layer.srt	2.1 KB
5. Fully connected Layer.mp4	9.8 MB
5. Fully connected Layer.srt	2.0 KB
/~Get Your Files Here !/
Bonus Resources.txt	0.4 KB
Total files 116