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[DesireCourse Net] Udemy - Algorithmic Problems & Neural Networks in Python
Torrent info
Torrent Files List
1. Introduction (Size: 826.48 MB) (Files: 115)
1. Introduction
1. Introduction.mp4
1. Introduction.vtt
2. Backtracking
1. Backtracking introduction.mp4
1. Backtracking introduction.vtt
10. Knight tour implementation.mp4
10. Knight tour implementation.vtt
11. UPDATE Knight's Tour.html
12. Maze problem introduction.mp4
12. Maze problem introduction.vtt
13. Maze problem implementation.mp4
13. Maze problem implementation.vtt
14. NP-complete problems.mp4
14. NP-complete problems.vtt
2. N-queens problem introduction.mp4
2. N-queens problem introduction.vtt
3. N-queens problem implementation.mp4
3. N-queens problem implementation.vtt
4. Hamiltonian cycle introduction.mp4
4. Hamiltonian cycle introduction.vtt
5. Hamiltonian cycle illustration.mp4
5. Hamiltonian cycle illustration.vtt
6. Hamiltonian cycle implementation.mp4
6. Hamiltonian cycle implementation.vtt
7. Coloring problem introduction.mp4
7. Coloring problem introduction.vtt
8. Coloring problem implementation.mp4
8. Coloring problem implementation.vtt
9. Knight tour introduction.mp4
9. Knight tour introduction.vtt
3. Dynamic Programming
1. Dynamic programming introduction.mp4
1. Dynamic programming introduction.vtt
10. Rod cutting problem introduction.mp4
10. Rod cutting problem introduction.vtt
11. Rod cutting problem example.mp4
11. Rod cutting problem example.vtt
12. Rod cutting problem implementation.mp4
12. Rod cutting problem implementation.vtt
2. Fibonacci numbers introduction.mp4
2. Fibonacci numbers introduction.vtt
3. Fibonacci numbers implementation.mp4
3. Fibonacci numbers implementation.vtt
4. Knapsack problem introduction.mp4
4. Knapsack problem introduction.vtt
5. Knapsack problem example.mp4
5. Knapsack problem example.vtt
6. Knapsack problem implementation.mp4
6. Knapsack problem implementation.vtt
7. Coin change problem introduction.mp4
7. Coin change problem introduction.vtt
8. Coin change problem example.mp4
8. Coin change problem example.vtt
9. Coin change problem implementation.mp4
9. Coin change problem implementation.vtt
4. Neural Network Theory
1. ---------- NEURAL NETWORKS INTRODUCTION ----------.html
10. ---------- BACKPROPAGATION ----------.html
11. Feedforward neural networks.mp4
11. Feedforward neural networks.vtt
12. Optimization - cost function.mp4
12. Optimization - cost function.vtt
13. Simplified feedforward network.mp4
13. Simplified feedforward network.vtt
14. Feedforward neural network topology.mp4
14. Feedforward neural network topology.vtt
15. The learning algorithm.mp4
15. The learning algorithm.vtt
16. Error calculation.mp4
16. Error calculation.vtt
17. Gradient calculation I - output layer.mp4
17. Gradient calculation I - output layer.vtt
18. Gradient calculation II - hidden layer.mp4
18. Gradient calculation II - hidden layer.vtt
19. Backpropagation.mp4
19. Backpropagation.vtt
2. Axons and neurons in the human brain.mp4
2. Axons and neurons in the human brain.vtt
20. Backpropagation II.mp4
20. Backpropagation II.vtt
21. Applications of neural networks I - character recognition.mp4
21. Applications of neural networks I - character recognition.vtt
22. Applications of neural networks II - stock market forecast.mp4
22. Applications of neural networks II - stock market forecast.vtt
23. Deep learning.mp4
23. Deep learning.vtt
3. Modeling human brain.mp4
3. Modeling human brain.vtt
4. Learning paradigms.mp4
4. Learning paradigms.vtt
5. Artificial neurons - the model.mp4
5. Artificial neurons - the model.vtt
6. Artificial neurons - activation functions.mp4
6. Artificial neurons - activation functions.vtt
7. Artificial neurons - an example.mp4
7. Artificial neurons - an example.vtt
8. Neural networks - the big picture.mp4
8. Neural networks - the big picture.vtt
9. Applications of neural networks.mp4
9. Applications of neural networks.vtt
5. Neural Network Implementation
1. Neural network implementation - representations.mp4
1. Neural network implementation - representations.vtt
2. Neural network implementation - helper methods.mp4
2. Neural network implementation - helper methods.vtt
3. Neural network implementation - initialize.mp4
3. Neural network implementation - initialize.vtt
4. Neural network implementation - feedforward.mp4
4. Neural network implementation - feedforward.vtt
5. Neural network implementation - backpropagation.mp4
5. Neural network implementation - backpropagation.vtt
6. Neural network implementation - mean squared error.mp4
6. Neural network implementation - mean squared error.vtt
7. Neural network implementation - testing.mp4
7. Neural network implementation - testing.vtt
6. Course Materials (DOWNLOADS)
1. Course material.html
7. BONUS
1. DISCOUNT FOR OTHER COURSES!.html
[CourseClub.Me].url
[DesireCourse.Net].url
Torrent description
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