I'm new to data structures and I have to build a rough version of Uber using graph, Floyd Warshall algorithm and search tree I think. Are there any similar problems and can I get some guidance on how to tackle this? Thanks
I would check out google maps api.
Its a fast easy way to get started on the mapping side.
Here's a link to get started
https://developers.google.com/maps/documentation/javascript/tutorial
Related
Hi I just came from milr doc and got quiet confused.
I tried to work through the toy project, but cannot understand the mechanism and concept of dialect.
The tutorial just offered an example of some code, how they would interact with each other, how should I use them, it mentioned nothing.
As a beginner, I'm really lost and do not know what to do.
May someone please help me on how to compile a simple program that transfer source to mlir, using the current framework it provided.
The easiest way to learn is by doing some projects. For MLIR, I think you can start by first understanding and doing the Toy tutorial
Then see if you can extend it by adding a new operation to this toy language. If you found this interesting, try out a dialect conversion exercise (say toy to SCF).
TL;DR i'm currently creating a cross-platform mobile news aggregator, which will identify news articles from different publishers, but about the same topic, e.g. a celebrity passes away.
I believe I found an appropriate journal that can guide me through the steps 'Document Clustering with grouping and chaining algorithms'.
(https://www.aclweb.org/anthology/I05-1025.pdf)
However many of the steps are confusing me such as:
1) Document clustering
2) Grouping and chaining algorithms
3) Understanding equations such as the one below that I'll need to compute.
Any help on the matter, or a brief description of the steps would be greatly appreciated.
Thanks for the help.
I'm also interested in any experts in this field, and would love to use your knowledge as qualitative evidence for my project. If you'd be be up for it please DM, or drop a comment. Thanks again!
During the practice when I am solving the graph problems I sometimes need to write lot of code ( Edge API, Graph API, Indexed Priority Queue in case of Dijkstra's shortest path algorithm). I don't want to sound lazy but this can become time consuming given the fact that I have written these API already and I know how to implement them. So should I maintain copy of these and just use them in the code whenever required so that it can save me time.
Can you suggest me the approach that has been successful for you?
Will really appreciate any help!
I would advice you to store these APIs somewhere (e.g. IDE, Github) where you have quick access on them and copy them.
I am new to JuMP / Julia. Do you have some suggestions or advice about how to learn it given that there are so few resources on the internet ?
Go to the fore mentioned quick start guide and run the examples.
JuliaCon lectures are also a good source of information and can be found on YouTube.
Once you get through there is a collection of JuMP notebooks at JuliaOpt.
Using JuMP is simple. However, difficulty might arise due to frequent changes to APIs and interoperability between versions (sometimes you will come across an example that just does not work).
I am new to ArangoDB and have been reading through the documentation and examples available online for a few days now. However, I am not able to formulate a query to do a complex calculation using AQL. Looking forward to some examples that can help.
For starters, an idea on what's the best way to solve a case such as: http://neo4j.com/docs/stable/cypher-cookbook-similarity-calc.html#d5e4728 would be very helpful.
Thanks in advance!
You're right. Our documentation is lacking examples, we will fix this. Its used like that:
db._query('RETURN SUM([1,3,5*7])/3.5')
[
11.142857142857142
]