Answer:
40
Explanation:
Given that:
A neural network with 11 input variables possess;
one hidden layer with three hidden units; &
one output variable
For every input, a variable must go to every node.
Thus, we can calculate the weights of weight with respect to connections to input and hidden layer by using the formula:
= ( inputs + bias) × numbers of nodes
= (11 + 1 ) × 3
= 12 × 3
= 36 weights
Also, For one hidden layer (with 3 nodes) and one output
The entry result for every hidden node will go directly to the output
These results will have weights associated with them before computed in the output node.
Thus; using the formula
= (numbers of nodes + bais) output, we get;
= ( 3+ 1 ) × 1
= 4 weights
weights with respect to input and hidden layer total = 36
weights with respect to hidden and output layer total = 4
Finally, the sum of both weights is = 36 + 4
= 40
That's really really hard, my god Cassie!
Explanation:
I don't know what the answer is. bekos Yu du not is da layer of da peyk Cassie. di ka mukhang dragon
Zoom to selection is the command that should be used to increase or decrease the view of a selected cell or range of cells to fill the excel window area for better visibility
I hope this will help you.
Answer:
DynamoDB is the correct answer of this question.
Explanation:
DynamoDB is a completely controlled NoSQL server website that allows server tables to be generated that can store and recover any amount of information.DynamoDB is an Amazon Web Services server platform that promotes software architectures and web resources priced by key.
DynamoDB can accommodate over 10 billions requests in a day, and therefore can sustain peaks of over 20 million queries per second.
The errror that has occured is a False Positive error.
Explanation:
- A false positive is where you receive a positive result for a test, when you should have received a negative results.
- A false positive (type I error) — when you reject a true null hypothesis.
- The type I error rate or significance level is the probability of rejecting the null hypothesis given that it is true. It is denoted by the Greek letter alpha
