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Neural Threads
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1:16
4.4 What is Binary cross-entropy loss and how to compute the gradients?
1:01
4.3 What is Categorical cross-entropy loss and how to compute the gradients?
0:43
4.2 Mean absolute error and how to calculate its derivative?
0:43
4.1 Mean square error and how to calculate its derivative?
1:22
3.7 What is Softmax Activation function and how to take its Derivative or Jacobian?
0:31
3.6 What is Softplus function and its derivative?
0:31
3.5 What is SELU and ELU functions and their derivatives?
0:37
3.4 What is ReLU and Leaky ReLU functions and their derivatives?
0:37
3.3 What is Softsign function and its derivative?
0:34
3.2 What is Tanh function and its derivative?
0:46
3.1 What is Sigmoid function and its derivative?
2:19
2.10 Optimizers racing to the Minima
2:11
2.9 How does Adamax works?
2:23
2.8 How does Amsgrad works?
2:11
2.7 How does ADAM works?
2:23
2.6 How does Adadelta works?
1:53
2.5 How does RMSprop works?
1:50
2.4 How does Adagrad works?
1:56
2.3 What is SGD with Nesterov acceleration?
2:02
2.2 What is SGD with Momentum?
3:11
2.1 What is SGD or Stochastic Gradient Descent?
2:37
1.3 Some useful NumPy operations
2:19
1.2 What is Tensor reshaping?
3:22
1.1 What are Tensors? (Tensors as NumPy arrays)
0:52
0 Welcome to Neural Threads - Your total guide to Deep Learning
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