dreadlock | High-Speed Locking Daemon

by jamwt C Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | dreadlock Summary

dreadlock is a C library typically used in Networking applications. dreadlock has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Dreadlock is a simple + fast network-locking daemon. A client can connect to dreadlock over TCP and ensure exclusive access to a particular resource.

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Support

dreadlock has a low active ecosystem.

It has 8 star(s) with 0 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

dreadlock has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of dreadlock is current.

Quality

dreadlock has no bugs reported.

Security

dreadlock has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

dreadlock does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

dreadlock releases are not available. You will need to build from source code and install.

Installation instructions are not available. Examples and code snippets are available.

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dreadlock Key Features

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dreadlock Examples and Code Snippets

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Community Discussions

Trending Discussions on dreadlock

Gensim Word2Vec most similar different result python

QUESTION

Gensim Word2Vec most similar different result python

Asked 2018-Mar-21 at 09:51

I have the first Harry Potter book in txt format. From this, I created two new txt files: in the first, all the occurrencies of Hermione have been replaced with Hermione_1; in the second, all the occurrencies of Hermione have been replaced with Hermione_2. Then I concatenated these 2 text to create one long text and I used this as input for Word2Vec. This is my code:

...

ANSWER

Answered 2018-Mar-21 at 09:51

Training word2Vec models is random to an extent. That is why you may get different results. Also, Hermione_2 starts appearing in the second half of the text data. In my understanding over the course of processing the data when the Hermione_1 context is already established and so is the vector for this word you introduce a second word in exactly the same context and the algorithm tries to find what differentiates the two. Secondly, you use a very short vector which may under-represent the complexity of the conceptual space. Due to the simplifications you get two vectors without any overlap.

Source https://stackoverflow.com/questions/49402113

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install dreadlock

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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