种子简介
种子名称:
[DesireCourse.Net] Udemy - Algorithmic Problems & Neural Networks in Python
文件类型:
视频
文件数目:
54个文件
文件大小:
826.11 MB
收录时间:
2020-10-30 05:31
已经下载:
3次
资源热度:
252
最近下载:
2024-11-13 19:29
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[DesireCourse.Net] Udemy - Algorithmic Problems & Neural Networks in Python.torrent
1. Introduction/1. Introduction.mp44.23MB
2. Backtracking/1. Backtracking introduction.mp414.41MB
2. Backtracking/10. Knight tour implementation.mp421.08MB
2. Backtracking/12. Maze problem introduction.mp46.83MB
2. Backtracking/13. Maze problem implementation.mp420.72MB
2. Backtracking/14. NP-complete problems.mp49.01MB
2. Backtracking/2. N-queens problem introduction.mp422.6MB
2. Backtracking/3. N-queens problem implementation.mp429.04MB
2. Backtracking/4. Hamiltonian cycle introduction.mp421.71MB
2. Backtracking/5. Hamiltonian cycle illustration.mp413.19MB
2. Backtracking/6. Hamiltonian cycle implementation.mp424.79MB
2. Backtracking/7. Coloring problem introduction.mp422.01MB
2. Backtracking/8. Coloring problem implementation.mp417.49MB
2. Backtracking/9. Knight tour introduction.mp49.02MB
3. Dynamic Programming/1. Dynamic programming introduction.mp48.58MB
3. Dynamic Programming/10. Rod cutting problem introduction.mp412.73MB
3. Dynamic Programming/11. Rod cutting problem example.mp418.95MB
3. Dynamic Programming/12. Rod cutting problem implementation.mp414.59MB
3. Dynamic Programming/2. Fibonacci numbers introduction.mp413.42MB
3. Dynamic Programming/3. Fibonacci numbers implementation.mp411.98MB
3. Dynamic Programming/4. Knapsack problem introduction.mp431.23MB
3. Dynamic Programming/5. Knapsack problem example.mp430.08MB
3. Dynamic Programming/6. Knapsack problem implementation.mp418.71MB
3. Dynamic Programming/7. Coin change problem introduction.mp422.32MB
3. Dynamic Programming/8. Coin change problem example.mp413.57MB
3. Dynamic Programming/9. Coin change problem implementation.mp417.75MB
4. Neural Network Theory/11. Feedforward neural networks.mp418.41MB
4. Neural Network Theory/12. Optimization - cost function.mp425.88MB
4. Neural Network Theory/13. Simplified feedforward network.mp419.41MB
4. Neural Network Theory/14. Feedforward neural network topology.mp414.73MB
4. Neural Network Theory/15. The learning algorithm.mp413.25MB
4. Neural Network Theory/16. Error calculation.mp413.73MB
4. Neural Network Theory/17. Gradient calculation I - output layer.mp420.27MB
4. Neural Network Theory/18. Gradient calculation II - hidden layer.mp49.18MB
4. Neural Network Theory/19. Backpropagation.mp412.66MB
4. Neural Network Theory/2. Axons and neurons in the human brain.mp419.01MB
4. Neural Network Theory/20. Backpropagation II.mp44.67MB
4. Neural Network Theory/21. Applications of neural networks I - character recognition.mp48.77MB
4. Neural Network Theory/22. Applications of neural networks II - stock market forecast.mp49.52MB
4. Neural Network Theory/23. Deep learning.mp49.46MB
4. Neural Network Theory/3. Modeling human brain.mp416.05MB
4. Neural Network Theory/4. Learning paradigms.mp46.4MB
4. Neural Network Theory/5. Artificial neurons - the model.mp416.3MB
4. Neural Network Theory/6. Artificial neurons - activation functions.mp414.05MB
4. Neural Network Theory/7. Artificial neurons - an example.mp411.18MB
4. Neural Network Theory/8. Neural networks - the big picture.mp410.6MB
4. Neural Network Theory/9. Applications of neural networks.mp45.16MB
5. Neural Network Implementation/1. Neural network implementation - representations.mp410.11MB
5. Neural Network Implementation/2. Neural network implementation - helper methods.mp48.14MB
5. Neural Network Implementation/3. Neural network implementation - initialize.mp414.9MB
5. Neural Network Implementation/4. Neural network implementation - feedforward.mp413.43MB
5. Neural Network Implementation/5. Neural network implementation - backpropagation.mp424.45MB
5. Neural Network Implementation/6. Neural network implementation - mean squared error.mp48.87MB
5. Neural Network Implementation/7. Neural network implementation - testing.mp417.48MB