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[FTUForum.com] [UDEMY] Algorithmic Problems in Python [FTU]
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2019-7-23 20:18
2024-12-22 01:26
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906.62 MB
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UDEMY
Algorithmic
Problems
in
Python
FTU
文件列表
1. Introduction/1. Introduction.mp4
11.89MB
2. Backtracking/1. Backtracking introduction.mp4
14.41MB
2. Backtracking/10. Knight tour implementation.mp4
21.08MB
2. Backtracking/12. Maze problem introduction.mp4
6.83MB
2. Backtracking/13. Maze problem implementation.mp4
20.72MB
2. Backtracking/14. NP-complete problems.mp4
9.01MB
2. Backtracking/2. N-queens problem introduction.mp4
22.6MB
2. Backtracking/3. N-queens problem implementation.mp4
29.04MB
2. Backtracking/4. Hamiltonian cycle introduction.mp4
21.71MB
2. Backtracking/5. Hamiltonian cycle illustration.mp4
13.19MB
2. Backtracking/6. Hamiltonian cycle implementation.mp4
24.79MB
2. Backtracking/7. Coloring problem introduction.mp4
22.01MB
2. Backtracking/8. Coloring problem implementation.mp4
17.49MB
2. Backtracking/9. Knight tour introduction.mp4
9.02MB
3. Dynamic Programming/1. Dynamic programming introduction.mp4
8.58MB
3. Dynamic Programming/10. Rod cutting problem introduction.mp4
12.73MB
3. Dynamic Programming/11. Rod cutting problem example.mp4
18.95MB
3. Dynamic Programming/12. Rod cutting problem implementation.mp4
14.59MB
3. Dynamic Programming/2. Fibonacci numbers introduction.mp4
13.42MB
3. Dynamic Programming/3. Fibonacci numbers implementation.mp4
11.98MB
3. Dynamic Programming/4. Knapsack problem introduction.mp4
31.23MB
3. Dynamic Programming/5. Knapsack problem example.mp4
30.08MB
3. Dynamic Programming/6. Knapsack problem implementation.mp4
18.71MB
3. Dynamic Programming/7. Coin change problem introduction.mp4
22.32MB
3. Dynamic Programming/8. Coin change problem example.mp4
13.57MB
3. Dynamic Programming/9. Coin change problem implementation.mp4
17.75MB
4. Neural Network Theory/11. Feedforward neural networks.mp4
18.41MB
4. Neural Network Theory/12. Optimization - cost function.mp4
25.88MB
4. Neural Network Theory/13. Simplified feedforward network.mp4
19.41MB
4. Neural Network Theory/14. Feedforward neural network topology.mp4
14.73MB
4. Neural Network Theory/15. The learning algorithm.mp4
13.25MB
4. Neural Network Theory/16. Error calculation.mp4
13.73MB
4. Neural Network Theory/17. Gradient calculation I - output layer.mp4
20.27MB
4. Neural Network Theory/18. Gradient calculation II - hidden layer.mp4
9.18MB
4. Neural Network Theory/19. Backpropagation.mp4
12.66MB
4. Neural Network Theory/2. Axons and neurons in the human brain.mp4
19.01MB
4. Neural Network Theory/20. Backpropagation II.mp4
4.67MB
4. Neural Network Theory/21. Applications of neural networks I - character recognition.mp4
8.77MB
4. Neural Network Theory/22. Applications of neural networks II - stock market forecast.mp4
9.52MB
4. Neural Network Theory/23. Deep learning.mp4
9.46MB
4. Neural Network Theory/3. Modeling human brain.mp4
16.05MB
4. Neural Network Theory/4. Learning paradigms.mp4
6.4MB
4. Neural Network Theory/5. Artificial neurons - the model.mp4
16.3MB
4. Neural Network Theory/6. Artificial neurons - activation functions.mp4
14.05MB
4. Neural Network Theory/7. Artificial neurons - an example.mp4
11.18MB
4. Neural Network Theory/8. Neural networks - the big picture.mp4
10.6MB
4. Neural Network Theory/9. Applications of neural networks.mp4
5.16MB
5. Neural Network Implementation/1. Neural network implementation - representations.mp4
10.11MB
5. Neural Network Implementation/2. Neural network implementation - helper methods.mp4
8.14MB
5. Neural Network Implementation/3. Neural network implementation - initialize.mp4
14.9MB
5. Neural Network Implementation/4. Neural network implementation - feedforward.mp4
13.43MB
5. Neural Network Implementation/5. Neural network implementation - backpropagation.mp4
24.45MB
5. Neural Network Implementation/6. Neural network implementation - mean squared error.mp4
30.8MB
5. Neural Network Implementation/7. Neural network implementation - testing.mp4
68.41MB
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