Model_Log | Model Log 是一款基于 Python3 的轻量级机器学习(Machine Learning)、深度学习(Deep Learning)模型训练评估指标可视化工具，可以记录模型训练过程当中的超参数 | Machine Learning library

by NLP-LOVE Python Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | Model_Log Summary

Model_Log is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow, Keras applications. Model_Log 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 Model_Log' or download it from GitHub, PyPI.

Model Log 是一款基于 Python3 的轻量级机器学习(Machine Learning)、深度学习(Deep Learning)模型训练评估指标可视化工具，可以记录模型训练过程当中的超参数、Loss、Accuracy、Precision、F1值等，并以曲线图的形式进行展现对比，轻松三步即可实现。

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Quality

Security

License

Reuse

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Model_Log has a low active ecosystem.

It has 115 star(s) with 38 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 1 have been closed. On average issues are closed in 57 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of Model_Log is current.

Quality

Model_Log has 0 bugs and 0 code smells.

Security

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

Model_Log code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Model_Log is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

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

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.

Model_Log saves you 1434 person hours of effort in developing the same functionality from scratch.

It has 3205 lines of code, 40 functions and 12 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Model_Log and discovered the below as its top functions. This is intended to give you an instant insight into Model_Log implemented functionality, and help decide if they suit your requirements.

Detail of a project
Generate loss data
Delete model from database
Generate table data
Add a metric to the model
Check if given model name exists in project table
Check if model_name is in project_name
Add model data
Render the index page
Check for login
Delete models
Delete all sub_model_params
Generate new data
Generate data_list_loss for a sub - model
Get project list
Get page number
Mark model as finished
Login to project
Delete sub models
Check if a new model has been created
Add a new best result to the model
Add a remark to the model
Add model_name
Add a parameter to the model
Creates a neural network

Get all kandi verified functions for this library.

Model_Log Key Features

No Key Features are available at this moment for Model_Log.

Model_Log Examples and Code Snippets

No Code Snippets are available at this moment for Model_Log.

Community Discussions

Trending Discussions on Model_Log

Text Classification with Python

AttributeError: 'Sequential' object has no attribute '_get_distribution_strategy'

Error while converting continuous data to categorical data in Logistic Regression

Execute function in C++ after asyncranous 60 sec delay?

QUESTION

Text Classification with Python

Asked 2020-Oct-14 at 17:34

HI i am new to python programming language, based on the various reference i have build the text classification model using logistic regression, Below is the code.

...

ANSWER

Answered 2020-Oct-14 at 17:34

Please try:

Source https://stackoverflow.com/questions/64353644

QUESTION

AttributeError: 'Sequential' object has no attribute '_get_distribution_strategy'

Asked 2020-May-02 at 06:50

I am following an online course through linkedin regrading the Building of models through Keras.

This is my code. (This is claimed to work)

...

ANSWER

Answered 2020-Feb-13 at 09:46

You may find this post useful.

So instead of importing from keras (i.e.)

Source https://stackoverflow.com/questions/59765784

QUESTION

Error while converting continuous data to categorical data in Logistic Regression

Asked 2020-Mar-23 at 06:29

I am using Logistic regression over my dataset which has its target variable in 0s and 1s. I used .replace() function and replaced them accordingly.

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ANSWER

Answered 2020-Mar-23 at 06:29

when you select X data using iloc,it is return a pandas dataframe.According to statsmodel documentation,logit expect to X and y to be array_like. You need to cast the dataframe to required data type.You can use to_numpy method to convert dataframe to numpy array.

Source https://stackoverflow.com/questions/60796470

QUESTION

Execute function in C++ after asyncranous 60 sec delay?

Asked 2018-May-15 at 10:06

I've read this can be achieved using std::this_thread::sleep_for and std::async, but it's not working for me.

Here is the function to be called:

...

ANSWER

Answered 2018-May-15 at 10:06

Because refresh_data is a method of Log you need to use std::bind with model_log, or use a lambda:

Source https://stackoverflow.com/questions/50347314

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

Vulnerabilities

No vulnerabilities reported

Install Model_Log

You can install using 'pip install Model_Log' or download it from GitHub, PyPI.
You can use Model_Log 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 .

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