activation relu tanh | How to Choose an Activation Function for Deep L

Keyword	CPC	PCC	Volume	Score	Length of keyword
activation relu tanh	1.9	0.9	7271	22	20
activation	0.33	0.5	391	97	10
relu	0.4	0.3	9670	88	4
tanh	1.15	0.5	7924	41	4

Keyword	CPC	PCC	Volume	Score
activation relu tensorflow	1.42	0.2	8748	30
tanh vs relu activation	0.93	0.1	4510	62
relu vs tanh activation function	1.14	0.7	3844	31
sigmoid tanh relu activation function	1.98	0.7	8590	44
activation functions sigmoid relu tanh	0.28	0.1	10000	71
is relu better than tanh	0.57	0.7	5489	66
combine relu with tanh	1.63	0.9	8317	27
swish activation function vs relu	1.88	0.7	9698	38
tanh-relu	1.2	0.6	6326	91
tanh formula activation function	1.55	1	2167	37
tanh activation function code	1.78	0.9	2308	2
tanh activation function range	0.7	0.9	4701	82
relu vs sigmoid vs tanh	1	0.1	8126	19
when to use tanh activation function	1.35	0.7	2985	59
tanh activation function equation	0.69	1	2132	87
tanh activation function in deep learning	1.86	0.8	5437	93
tanh activation function derivative	0.66	0.9	722	87
tanh activation function in neural network	0.05	0.2	2122	30
types of relu activation function	0.58	0.2	759	85
relu activation function example	1.57	1	2593	24
leaky relu activation function tensorflow	0.24	0.7	8059	47
tensorflow leaky relu activation	0.85	0.9	1330	43
relu activation function tensorflow	1.72	0.9	1260	75
tensorflow activation functions leaky relu	0.48	0.5	5115	69

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