I’ve been using 18.04 server for several months to host a few services. I’ve recently started diving into Docker and in many of the guides I encounter they give command line calls that use NetworkManager, which is not installed with server. This is annoying to the point I’m asking myself why I’m not using Desktop.
I chose the server flavor mostly because I like the geekiness of the command line. I also figured it is less resource intensive than it’s Desktop counterpart. While I know I can install Desktop and still use the command line, but what am I “saving” by using Server over Desktop, especially if both versions use the same kernel?
If I’m using the machine as a server, how much is Desktop costing me in terms of resources and performance?
When would one choose to use the Masquerade module and when the Devel sub module Switch User? What are some of the most crucial benefits for each?
Looking for information on choosing a heuristic for instances where the cost of traversing an edge can be less than one.
For example, say movement is allowed in the cardinal directions. Should all edge costs be at least one, then I would consider diagonal distance. However, if costs can be less than one, this could lead to an instance where diagonal distance will be an overestimate and thus is not an admissible heuristic.
My thought on the matter is perhaps to find the smallest possible cost and figure out a constant to divide diagonal distance by to guarantee it will never overestimate?
Would appreciate some guidance or some resources to look further into this.
My machine tends to switch arbitrarily to wifi when my laptop is connected to ethernet. I’m wondering how I can prevent this.
I came across two web development courses recently, wanted to know which one of them is more useful and in demand recently.
I want to opt for course which teaches to be a full stack web developer but I am confused. With course A it seems desktop only web and course b seems mobile only, is it correct? Also whats the difference between the two course and which path do they lead to.
I have a NN that has ten outputs. The output values range between 0 and 1. The elements in the target array are all zeros except one element, which is “one”.
I am searching for a Fitness Function that will correctly evaluate (score) the Neural Networks.
Currently, I am trying to calculate the distance between the target and the output arrays. The issue is that at the beginning all my NNs return results that are very close to each other and I can’t properly choose the fittest individuals.
NN1 -> FF score:0.10030096 -> Rank? NN2 -> FF score:0.09996143 -> Rank? NN3 -> FF score:0.10015215 -> Rank?
I’ve been using the CH criterion to determine the optimal number of clusters for some data I’m working with. I know that in general you would evaluate the criterion for a number of different choices of clusters, and choose the number of clusters which gives the highest CH value, or one where there is a large increase in CH score.
For my data, the optimal number of clusters is 2. Plotting the CH score against number of clusters, I can see the score decreases very quickly if you increase the number of clusters.
My question is this: Since the CH criterion does not evaluate for 1 cluster, how can I be sure using 2 clusters is better than one cluster? I.e how can one determine if there is evidence for any clustering at all in the data?
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There are two providers of resellers hosting:-
What I’m getting with ResellersPanel:-
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