Macadam | Macadam是一个以Tensorflow | Natural Language Processing library
kandi X-RAY | Macadam Summary
kandi X-RAY | Macadam Summary
Macadam is a Python library typically used in Artificial Intelligence, Natural Language Processing, Pytorch, Tensorflow, Keras, Bert, Neural Network applications. Macadam has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install Macadam' or download it from GitHub, PyPI.
Macadam
Macadam
Support
Quality
Security
License
Reuse
Support
Macadam has a low active ecosystem.
It has 222 star(s) with 30 fork(s). There are 7 watchers for this library.
It had no major release in the last 12 months.
There are 0 open issues and 2 have been closed. On average issues are closed in 0 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of Macadam is 0.1.1
Quality
Macadam has 0 bugs and 0 code smells.
Security
Macadam has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
Macadam code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
Macadam is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
Macadam releases are available to install and integrate.
Deployable package is available in PyPI.
Build file is available. You can build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Macadam saves you 2091 person hours of effort in developing the same functionality from scratch.
It has 4589 lines of code, 227 functions and 83 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed Macadam and discovered the below as its top functions. This is intended to give you an instant insight into Macadam implemented functionality, and help decide if they suit your requirements.
- Train the model
- Create TensorBoard callback
- Create the model
- Fit the model
- Builds the embedding
- Build tokenizer
- Cut text from string
- Get list of ngrams from text
- Predict embedding
- Return the path of the viterbi decomposition
- Preprocess the x - index
- Builds an embedding model
- Build the configuration
- Evaluate the prediction
- Predict a list of texts
- Builds a vocabulary
- Sort a dictionary
- Iterate over the model
- Iterate through all the items in fit
- Encodes the given text
- Write lines to txt file
- Convert y to categorical label
- Load tokenizer
- Build the model
- Build a transformer model
- Calculate metrics after prediction
Get all kandi verified functions for this library.
Macadam Key Features
No Key Features are available at this moment for Macadam.
Macadam Examples and Code Snippets
No Code Snippets are available at this moment for Macadam.
Community Discussions
Trending Discussions on Macadam
QUESTION
Get XML data with random Id nodes
Asked 2017-Mar-22 at 15:43
I would like to read a specific node of my XML but I am having problems on how to focus the problem.
Right now the XML file has this structure:
...ANSWER
Answered 2017-Mar-22 at 15:43You can use LINQ to XML which have little bid easy to understand API and better readability
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Macadam
You can install using 'pip install Macadam' or download it from GitHub, PyPI.
You can use Macadam like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
You can use Macadam like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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 .
Find more information at:
Reuse Trending Solutions
Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items
Find more librariesStay Updated
Subscribe to our newsletter for trending solutions and developer bootcamps
Share this Page
