Questions in this topic

1. What does it mean if derivatives of parameters with respect to cost is negative?
2. Is the line that separates y 0 and y 1 in a logistic function?
3. Which of these is a benefit of batch normalization?
4. What is the formula for calculating cost function?
5. Can cost function be zero?
6. What is S shaped curve?
7. What is the cost function in machine learning?
8. What is weight Ann?
9. What is weight initialization neural network?
10. What is Xavier initialization?
11. Why batch normalization is used?
12. Why does Xavier initialization work?
13. Why is batch normalization important?
14. Why is normalization important?
15. Why is Softmax called Softmax?
16. Why is Softmax used?
17. Why we use sigmoid function in logistic regression?
18. What is minimize cost?
19. What is J in machine learning?
20. What is hidden layer?
21. Can I initialize a disk without losing data?
22. Can loss function negative?
23. Does it make sense to initialize all weights in a deep network to 0 justify?
24. How do I find the hidden layer size?
25. How do I initialize an unallocated disk?
26. How does batch normalization help optimization?
27. How does batch normalization work?
28. How many hidden layers are there?
29. Is NTFS MBR or GPT?
30. What does Batch Norm do?
31. What does sigmoidal curve mean?
32. What does Softmax mean?
33. What is disk initialization?
34. What is dying ReLU?
35. Will disk initialization erase data?