machinelearning | open source and cross-platform machine learning framework | Machine Learning library

by dotnet C# Version: v3.0.0-Preview License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | machinelearning Summary

machinelearning is a C# library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. machinelearning has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

ML.NET is an open source and cross-platform machine learning framework for .NET.

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machinelearning has a medium active ecosystem.

It has 8457 star(s) with 1823 fork(s). There are 593 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 794 open issues and 2773 have been closed. On average issues are closed in 75 days. There are 14 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of machinelearning is v3.0.0-Preview

Quality

machinelearning has 0 bugs and 0 code smells.

Security

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

machinelearning code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

machinelearning 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

machinelearning releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

machinelearning saves you 361 person hours of effort in developing the same functionality from scratch.

It has 862 lines of code, 2 functions and 1546 files.

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

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machinelearning Key Features

No Key Features are available at this moment for machinelearning.

machinelearning Examples and Code Snippets

No Code Snippets are available at this moment for machinelearning.

Community Discussions

Trending Discussions on machinelearning

ML.NET KMeans clustering - What is the Davies Boulding Index?

Unpickle instance from Jupyter Notebook in Flask App

venv - pip not found

Why embarkation_point_2 field gets added when one_hot_encoder is applied to training data

How to seldon-core quick-start on kind with port-forward?

Accord.NET throw "Index was outside the bounds of the array"

Seldon Core Loading sklearn/irir failed

"bash: export: ... not a valid identifier" in CLI of git-bash shell "MINGW64" on Windows 10

How to import kaggle datasets to PyCharm IDE

Possible to select the DNN AI core for model evaluation on HoloLens 2?

QUESTION

ML.NET KMeans clustering - What is the Davies Boulding Index?

Asked 2022-Mar-15 at 22:34

I am using the KMeans clustering algorithm from ML.NET (here) and when evaluating the model, I see Davies Bouldin Index in the model metrics.

What is the range of this index? What does its value of zero mean?

...

ANSWER

Answered 2022-Mar-15 at 22:34

According to the documentation the Davies Bouldin Index is:

"The average ratio of within-cluster distances to between-cluster distances. The tighter the cluster, and the further apart the clusters are, the lower this value is." Also:

"Values closer to 0 are better. Clusters that are farther apart and less dispersed will result in a better score." You can find more information on the Davies Bouldin Index in the following here.

Source https://stackoverflow.com/questions/71424036

QUESTION

Unpickle instance from Jupyter Notebook in Flask App

Asked 2022-Feb-28 at 18:03

I have created a class for word2vec vectorisation which is working fine. But when I create a model pickle file and use that pickle file in a Flask App, I am getting an error like:

AttributeError: module '__main__' has no attribute 'GensimWord2VecVectorizer'

I am creating the model on Google Colab.

Code in Jupyter Notebook:

...

ANSWER

Answered 2022-Feb-24 at 11:48

Import GensimWord2VecVectorizer in your Flask Web app python file.

Source https://stackoverflow.com/questions/71231611

QUESTION

venv - pip not found

Asked 2021-Dec-14 at 15:04

I am using Windows 10 & Python 3.9
I am new to Python, after I created venv and facing the following errors:
My venv is able to catch the pip path when I use the command where pip. Which is in F drive
...

ANSWER

Answered 2021-Dec-14 at 15:04

My problem is resolved.
Instead of using pip install just need to use python -m pip install , within venv to avoid the following error

Source https://stackoverflow.com/questions/70321475

QUESTION

Why embarkation_point_2 field gets added when one_hot_encoder is applied to training data

Asked 2021-Dec-03 at 14:44

Following the example of vertica at https://www.vertica.com/docs/11.0.x/HTML/Content/Authoring/AnalyzingData/MachineLearning/DataPreparation/EncodingCategoricalColumns.htm?tocpath=Analyzing%20Data%7CMachine%20Learning%20for%20Predictive%20Analytics%7CData%20Preparation%7C_____3

which uses Titanic data from kaggle,

ONE_HOT_ENCODER_FIT function coverts categorical data and creates a model which represents the new representation of categorical data

...

ANSWER

Answered 2021-Dec-03 at 14:44

There are many reasons to your output. First, read the documentation of the APPLY_ONE_HOT_ENCODER: https://www.vertica.com/docs/11.0.x/HTML/Content/Authoring/SQLReferenceManual/Functions/MachineLearning/APPLY_ONE_HOT_ENCODER.htm?tocpath=SQL%20Reference%20Manual%7CSQL%20Functions%7CMachine%20Learning%20Functions%7CTransformation%20Functions%7C_____5

Two parameters allow you to achieve your goals:

drop_first: set it to false to get all the columns. One is dropped because of correlations purposes. You can read this article: https://inmachineswetrust.com/posts/drop-first-columns/ There are pros and cons.
column_naming: set it to values but be careful. If you have categories with special characters, you might face some difficulties.

Badr

Source https://stackoverflow.com/questions/70206239

QUESTION

How to seldon-core quick-start on kind with port-forward?

Asked 2021-Oct-13 at 10:50

Following the documentation I try to setup the Seldon-Core quick-start https://docs.seldon.io/projects/seldon-core/en/v1.11.1/workflow/github-readme.html

I don't have LoadBalancer so I would like to use port-fowarding for accessing to the service.

I run the following script for setup the system:

...

ANSWER

Answered 2021-Oct-13 at 10:50

If you install with istio enabled you also need to install the istio gateway.

I've tested your flow and it didn't work, and then did work after installing the following istio gateway.

Source https://stackoverflow.com/questions/69538672

QUESTION

Accord.NET throw "Index was outside the bounds of the array"

Asked 2021-Sep-27 at 18:03

I was working on KNN from Accord.NET and I faced this error for some reason when I need to test model.

but this error message didn't help at all (Index was outside the bounds of the array) because this error happen in the library itself.

simple code with random data:

...

ANSWER

Answered 2021-Sep-27 at 18:03

after many days and after implementing this simple sample I found that output array should have continues range values (encoded : 0,1,2,3,....) . so here 9 is why that bug happen here 🙂

Source https://stackoverflow.com/questions/69339578

QUESTION

Seldon Core Loading sklearn/irir failed

Asked 2021-Sep-06 at 12:46

I tried to load the iris model using seldon core, and unfortunately the following error occurred. SKLEARN_SERVER loads seldon’s sklearn/iris model with the following error.

...

ANSWER

Answered 2021-Sep-06 at 12:46

This is because the version of the seldon core does not match the version of the model. Note that the example model for seldon-core version 1.10.0 is under gs://seldon-models/v1.11.0-dev.

Source https://stackoverflow.com/questions/69023624

QUESTION

"bash: export: ... not a valid identifier" in CLI of git-bash shell "MINGW64" on Windows 10

Asked 2021-Jul-12 at 08:58

Using git for Windows, I always get the following output when opening a new git-bash terminal:

...

ANSWER

Answered 2021-Jul-12 at 08:58

As correctly pointed out in the first comment under my OP by @Zilog80, I had to check and remove all $ after the export-command in the following bash start-up scripts:

.bashrc
.bash_profile
.profile

In my case, all the fuss boiled down to the following line in my ~/.bashrc - script:

Source https://stackoverflow.com/questions/68344089

QUESTION

How to import kaggle datasets to PyCharm IDE

Asked 2021-Jul-05 at 20:18

I'm able to download kaggle using PIP command. Able to place the kaggle.json file into the appropriate folder. Able to see the competitions present in it. But when I'm trying to download the data files then an error getting displayed.

CODE:

...

ANSWER

Answered 2021-Jul-05 at 20:18

The error returned describes the root of the issue:

Source https://stackoverflow.com/questions/68248286

QUESTION

Possible to select the DNN AI core for model evaluation on HoloLens 2?

Asked 2021-Jun-07 at 17:27

Can anyone tell me if one can directly select the DNN AI core for neural network evaluation on HoloLens 2.

I have read about the HPU, which includes and DNN AI core in the GitHub repo here. But in the doc for the devices that can be used only CPU and GPU are listed.

...

ANSWER

Answered 2021-Jun-07 at 17:27

Currently Windows AI only supports inference on CPUs or GPUs.

Unfortunately there isn't a way to perform inference on the HoloLens2 HPU DNN AI Core at the moment.

Source https://stackoverflow.com/questions/66347068

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

Vulnerabilities

No vulnerabilities reported

Install machinelearning

Learn more about the basics of ML.NET.
Build your first ML.NET model by following our ML.NET Getting Started tutorial.
Check out our documentation and tutorials.
See the API Reference documentation.
Clone our ML.NET Samples GitHub repo and run some sample apps.
Take a look at some ML.NET Community Samples.
Watch some videos on the ML.NET videos YouTube playlist.

Support

ML.NET runs on Windows, Linux, and macOS using .NET Core, or Windows using .NET Framework. ML.NET also runs on ARM64, Apple M1, and Blazor Web Assembly. However, there are some limitations. 64-bit is supported on all platforms. 32-bit is supported on Windows, except for TensorFlow and LightGBM related functionality.

Find more information at: