[DesireCourse.Net] Udemy - Algorithmic Problems & Neural Networks in Python

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[DesireCourse.Net] Udemy - Algorithmic Problems & Neural Networks in Python

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种子哈希：e26b68d7489deeb91f0c502ba9c1eab4d64fe2c7
文件大小：826.48M
已经下载：872次
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收录时间：2021-03-22
最近下载：2025-05-04

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文件列表

  • 3. Dynamic Programming/4. Knapsack problem introduction.mp4 32.7 MB
  • 3. Dynamic Programming/5. Knapsack problem example.mp4 31.5 MB
  • 2. Backtracking/3. N-queens problem implementation.mp4 30.4 MB
  • 4. Neural Network Theory/12. Optimization - cost function.mp4 27.1 MB
  • 2. Backtracking/6. Hamiltonian cycle implementation.mp4 26.0 MB
  • 5. Neural Network Implementation/5. Neural network implementation - backpropagation.mp4 25.6 MB
  • 2. Backtracking/2. N-queens problem introduction.mp4 23.7 MB
  • 3. Dynamic Programming/7. Coin change problem introduction.mp4 23.4 MB
  • 2. Backtracking/7. Coloring problem introduction.mp4 23.1 MB
  • 2. Backtracking/4. Hamiltonian cycle introduction.mp4 22.8 MB
  • 2. Backtracking/10. Knight tour implementation.mp4 22.1 MB
  • 2. Backtracking/13. Maze problem implementation.mp4 21.7 MB
  • 4. Neural Network Theory/17. Gradient calculation I - output layer.mp4 21.3 MB
  • 4. Neural Network Theory/13. Simplified feedforward network.mp4 20.4 MB
  • 4. Neural Network Theory/2. Axons and neurons in the human brain.mp4 19.9 MB
  • 3. Dynamic Programming/11. Rod cutting problem example.mp4 19.9 MB
  • 3. Dynamic Programming/6. Knapsack problem implementation.mp4 19.6 MB
  • 4. Neural Network Theory/11. Feedforward neural networks.mp4 19.3 MB
  • 3. Dynamic Programming/9. Coin change problem implementation.mp4 18.6 MB
  • 2. Backtracking/8. Coloring problem implementation.mp4 18.3 MB
  • 5. Neural Network Implementation/7. Neural network implementation - testing.mp4 18.3 MB
  • 4. Neural Network Theory/5. Artificial neurons - the model.mp4 17.1 MB
  • 4. Neural Network Theory/3. Modeling human brain.mp4 16.8 MB
  • 5. Neural Network Implementation/3. Neural network implementation - initialize.mp4 15.6 MB
  • 4. Neural Network Theory/14. Feedforward neural network topology.mp4 15.4 MB
  • 3. Dynamic Programming/12. Rod cutting problem implementation.mp4 15.3 MB
  • 2. Backtracking/1. Backtracking introduction.mp4 15.1 MB
  • 4. Neural Network Theory/6. Artificial neurons - activation functions.mp4 14.7 MB
  • 4. Neural Network Theory/16. Error calculation.mp4 14.4 MB
  • 3. Dynamic Programming/8. Coin change problem example.mp4 14.2 MB
  • 5. Neural Network Implementation/4. Neural network implementation - feedforward.mp4 14.1 MB
  • 3. Dynamic Programming/2. Fibonacci numbers introduction.mp4 14.1 MB
  • 4. Neural Network Theory/15. The learning algorithm.mp4 13.9 MB
  • 2. Backtracking/5. Hamiltonian cycle illustration.mp4 13.8 MB
  • 3. Dynamic Programming/10. Rod cutting problem introduction.mp4 13.4 MB
  • 4. Neural Network Theory/19. Backpropagation.mp4 13.3 MB
  • 3. Dynamic Programming/3. Fibonacci numbers implementation.mp4 12.6 MB
  • 4. Neural Network Theory/7. Artificial neurons - an example.mp4 11.7 MB
  • 4. Neural Network Theory/8. Neural networks - the big picture.mp4 11.1 MB
  • 5. Neural Network Implementation/1. Neural network implementation - representations.mp4 10.6 MB
  • 4. Neural Network Theory/22. Applications of neural networks II - stock market forecast.mp4 10.0 MB
  • 4. Neural Network Theory/23. Deep learning.mp4 9.9 MB
  • 4. Neural Network Theory/18. Gradient calculation II - hidden layer.mp4 9.6 MB
  • 2. Backtracking/9. Knight tour introduction.mp4 9.5 MB
  • 2. Backtracking/14. NP-complete problems.mp4 9.4 MB
  • 5. Neural Network Implementation/6. Neural network implementation - mean squared error.mp4 9.3 MB
  • 4. Neural Network Theory/21. Applications of neural networks I - character recognition.mp4 9.2 MB
  • 3. Dynamic Programming/1. Dynamic programming introduction.mp4 9.0 MB
  • 5. Neural Network Implementation/2. Neural network implementation - helper methods.mp4 8.5 MB
  • 2. Backtracking/12. Maze problem introduction.mp4 7.2 MB
  • 4. Neural Network Theory/4. Learning paradigms.mp4 6.7 MB
  • 4. Neural Network Theory/9. Applications of neural networks.mp4 5.4 MB
  • 4. Neural Network Theory/20. Backpropagation II.mp4 4.9 MB
  • 1. Introduction/1. Introduction.mp4 4.4 MB
  • 2. Backtracking/3. N-queens problem implementation.vtt 14.8 kB
  • 3. Dynamic Programming/5. Knapsack problem example.vtt 14.3 kB
  • 3. Dynamic Programming/4. Knapsack problem introduction.vtt 14.2 kB
  • 2. Backtracking/2. N-queens problem introduction.vtt 12.4 kB
  • 4. Neural Network Theory/12. Optimization - cost function.vtt 12.1 kB
  • 2. Backtracking/6. Hamiltonian cycle implementation.vtt 11.4 kB
  • 2. Backtracking/7. Coloring problem introduction.vtt 11.1 kB
  • 3. Dynamic Programming/7. Coin change problem introduction.vtt 10.4 kB
  • 2. Backtracking/4. Hamiltonian cycle introduction.vtt 10.1 kB
  • 2. Backtracking/10. Knight tour implementation.vtt 10.0 kB
  • 4. Neural Network Theory/2. Axons and neurons in the human brain.vtt 9.6 kB
  • 3. Dynamic Programming/11. Rod cutting problem example.vtt 9.5 kB
  • 4. Neural Network Theory/17. Gradient calculation I - output layer.vtt 9.5 kB
  • 2. Backtracking/13. Maze problem implementation.vtt 9.3 kB
  • 4. Neural Network Theory/13. Simplified feedforward network.vtt 9.2 kB
  • 4. Neural Network Theory/11. Feedforward neural networks.vtt 9.1 kB
  • 5. Neural Network Implementation/5. Neural network implementation - backpropagation.vtt 9.0 kB
  • 3. Dynamic Programming/9. Coin change problem implementation.vtt 8.7 kB
  • 4. Neural Network Theory/3. Modeling human brain.vtt 8.6 kB
  • 2. Backtracking/8. Coloring problem implementation.vtt 8.1 kB
  • 3. Dynamic Programming/6. Knapsack problem implementation.vtt 8.1 kB
  • 4. Neural Network Theory/5. Artificial neurons - the model.vtt 7.4 kB
  • 2. Backtracking/1. Backtracking introduction.vtt 6.9 kB
  • 3. Dynamic Programming/12. Rod cutting problem implementation.vtt 6.9 kB
  • 2. Backtracking/5. Hamiltonian cycle illustration.vtt 6.7 kB
  • 4. Neural Network Theory/6. Artificial neurons - activation functions.vtt 6.7 kB
  • 3. Dynamic Programming/8. Coin change problem example.vtt 6.7 kB
  • 4. Neural Network Theory/14. Feedforward neural network topology.vtt 6.7 kB
  • 4. Neural Network Theory/16. Error calculation.vtt 6.7 kB
  • 3. Dynamic Programming/2. Fibonacci numbers introduction.vtt 6.5 kB
  • 4. Neural Network Theory/15. The learning algorithm.vtt 6.2 kB
  • 3. Dynamic Programming/10. Rod cutting problem introduction.vtt 6.2 kB
  • 5. Neural Network Implementation/7. Neural network implementation - testing.vtt 6.0 kB
  • 5. Neural Network Implementation/3. Neural network implementation - initialize.vtt 6.0 kB
  • 4. Neural Network Theory/19. Backpropagation.vtt 5.9 kB
  • 3. Dynamic Programming/3. Fibonacci numbers implementation.vtt 5.5 kB
  • 5. Neural Network Implementation/4. Neural network implementation - feedforward.vtt 5.5 kB
  • 4. Neural Network Theory/8. Neural networks - the big picture.vtt 5.0 kB
  • 5. Neural Network Implementation/1. Neural network implementation - representations.vtt 5.0 kB
  • 4. Neural Network Theory/22. Applications of neural networks II - stock market forecast.vtt 4.8 kB
  • 4. Neural Network Theory/7. Artificial neurons - an example.vtt 4.7 kB
  • 4. Neural Network Theory/23. Deep learning.vtt 4.7 kB
  • 2. Backtracking/14. NP-complete problems.vtt 4.6 kB
  • 4. Neural Network Theory/21. Applications of neural networks I - character recognition.vtt 4.5 kB
  • 2. Backtracking/9. Knight tour introduction.vtt 4.5 kB
  • 4. Neural Network Theory/18. Gradient calculation II - hidden layer.vtt 4.2 kB
  • 2. Backtracking/12. Maze problem introduction.vtt 4.2 kB
  • 5. Neural Network Implementation/6. Neural network implementation - mean squared error.vtt 4.0 kB
  • 3. Dynamic Programming/1. Dynamic programming introduction.vtt 3.9 kB
  • 5. Neural Network Implementation/2. Neural network implementation - helper methods.vtt 3.9 kB
  • 7. BONUS/1. DISCOUNT FOR OTHER COURSES!.html 3.8 kB
  • 4. Neural Network Theory/4. Learning paradigms.vtt 3.1 kB
  • 4. Neural Network Theory/9. Applications of neural networks.vtt 2.4 kB
  • 1. Introduction/1. Introduction.vtt 2.2 kB
  • 4. Neural Network Theory/20. Backpropagation II.vtt 2.1 kB
  • 2. Backtracking/11. UPDATE Knight's Tour.html 716 Bytes
  • 6. Course Materials (DOWNLOADS)/1. Course material.html 157 Bytes
  • [DesireCourse.Net].url 51 Bytes
  • [CourseClub.Me].url 48 Bytes
  • 4. Neural Network Theory/10. ---------- BACKPROPAGATION ----------.html 42 Bytes
  • 4. Neural Network Theory/1. ---------- NEURAL NETWORKS INTRODUCTION ----------.html 35 Bytes

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