FreeCourseLab com Udemy - Artificial Intelligence II - Neural Networks in Java

1. 1. Introduction/1. Introduction.mp46.95MB
2. 10. Classification - Iris Dataset/1. About the Iris dataset.mp47.12MB
3. 10. Classification - Iris Dataset/2. Constructing the neural network.mp48.03MB
4. 10. Classification - Iris Dataset/3. Testing the neural network.mp434.16MB
5. 11. Optical Character Recognition (OCR)/1. Optical character recognition theory.mp47.88MB
6. 11. Optical Character Recognition (OCR)/2. Installing paint.net.mp45.15MB
7. 11. Optical Character Recognition (OCR)/3. Transform an image into numerical data.mp49.83MB
8. 11. Optical Character Recognition (OCR)/4. Creating the datasets.mp47.64MB
9. 11. Optical Character Recognition (OCR)/5. OCR with neural network.mp443.94MB
10. 2. Neural Networks Introduction/1. Axons and neurons in the human brain.mp419.29MB
11. 2. Neural Networks Introduction/2. Modeling human brain.mp493.92MB
12. 2. Neural Networks Introduction/3. Learning paradigms.mp46.86MB
13. 2. Neural Networks Introduction/4. Artificial neurons - the model.mp416.55MB
14. 2. Neural Networks Introduction/5. Artificial neurons - activations functions.mp414.25MB
15. 2. Neural Networks Introduction/7. Artificial neurons - an example.mp411.37MB
16. 2. Neural Networks Introduction/8. Neural networks - the big picture.mp410.77MB
17. 2. Neural Networks Introduction/9. Applications of neural networks.mp45.23MB
18. 3. Hopfield Neural Network/1. Hopfield neural network introduction.mp411.76MB
19. 3. Hopfield Neural Network/2. Hopfield network energy.mp49.35MB
20. 3. Hopfield Neural Network/3. Hopfield neural network training and learning.mp411.55MB
21. 3. Hopfield Neural Network/4. Hopfield neural network problems.mp47.19MB
22. 3. Hopfield Neural Network/5. Hopfield neural network example.mp413.17MB
23. 3. Hopfield Neural Network/6. Hopfield network implementation I - utils.mp49.39MB
24. 3. Hopfield Neural Network/7. Hopfield network implementation II - matrix operations.mp419.06MB
25. 3. Hopfield Neural Network/8. Hopfield network implementation III - network.mp418.62MB
26. 3. Hopfield Neural Network/9. Hopfield network implementation IV - running the application.mp48.77MB
27. 4. Neural Networks With Backpropagation Theory/1. Feedforward neural networks.mp418.41MB
28. 4. Neural Networks With Backpropagation Theory/10. Backpropagation.mp412.67MB
29. 4. Neural Networks With Backpropagation Theory/11. Backpropagation II.mp44.67MB
30. 4. Neural Networks With Backpropagation Theory/13. Resilient propagation.mp418.56MB
31. 4. Neural Networks With Backpropagation Theory/14. Applications of neural networks I - character recognition.mp48.77MB
32. 4. Neural Networks With Backpropagation Theory/15. Applications of neural networks II - stock market forecast.mp49.52MB
33. 4. Neural Networks With Backpropagation Theory/16. Deep learning.mp49.46MB
34. 4. Neural Networks With Backpropagation Theory/2. Optimization - cost function.mp425.89MB
35. 4. Neural Networks With Backpropagation Theory/4. Simplified feedforward network.mp419.42MB
36. 4. Neural Networks With Backpropagation Theory/5. Feedforward neural network topology.mp414.72MB
37. 4. Neural Networks With Backpropagation Theory/6. The learning algorithm.mp413.25MB
38. 4. Neural Networks With Backpropagation Theory/7. Error calculation.mp413.73MB
39. 4. Neural Networks With Backpropagation Theory/8. Gradient calculation I - output layer.mp420.27MB
40. 4. Neural Networks With Backpropagation Theory/9. Gradient calculation II - hidden layer.mp49.17MB
41. 5. Types of Neural Networks/1. Types of neural networks.mp45.48MB
42. 6. Single Perceptron Model/1. Perceptron model training.mp44.67MB
43. 6. Single Perceptron Model/2. Perceptron model implementation I.mp411.54MB
44. 6. Single Perceptron Model/3. Perceptron model implementation II.mp412.83MB
45. 6. Single Perceptron Model/4. Perceptron model implementation III.mp413.67MB
46. 6. Single Perceptron Model/5. Trying to solve XOR problem.mp44.5MB
47. 6. Single Perceptron Model/6. Conclusion linearity and hidden layers.mp46.73MB
48. 7. Backpropagation Implementation/1. Structure of the feedforward network.mp413.12MB
49. 7. Backpropagation Implementation/2. Backpropagation implementation I - activation function.mp49.85MB
50. 7. Backpropagation Implementation/3. Backpropagation implementation II - NeuralNetwork.mp418.3MB
51. 7. Backpropagation Implementation/4. Backpropagation implementation III - Layer.mp412.07MB
52. 7. Backpropagation Implementation/5. Backpropagation implementation IV - run.mp416.42MB
53. 7. Backpropagation Implementation/6. Backpropagation implementation V - train.mp416.02MB
54. 8. Logical Operators/1. Logical operators introduction.mp44.62MB
55. 8. Logical Operators/2. Running the neural network AND.mp417.96MB
56. 8. Logical Operators/3. Running the neural network OR.mp48.06MB
57. 8. Logical Operators/4. Running the neural network XOR.mp45.56MB
58. 9. Clustering/1. Clustering with neural networks I.mp44.76MB
59. 9. Clustering/2. Clustering with neural networks II.mp413.49MB