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Feature Selection for Machine Learning
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Feature Selection for Machine Learning
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Feature Selection for Machine Learning Reviews & Product Details

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Feature Selection for Machine Learning Overview

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What is Feature Selection for Machine Learning?

The solution runs user specified feature selection tasks on input data and provides relevant features as output.

Feature Selection for Machine Learning Details
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Product Description

The solution runs user specified feature selection tasks on input data and provides relevant features as output.

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Mphasis

Description

Mphasis Stelligent, with its website located at https://stelligent.com/, specializes in providing DevOps automation and continuous delivery solutions on the Amazon Web Services (AWS) cloud platform. As part of Mphasis, a larger IT services company, Stelligent focuses on helping clients automate and accelerate the development, testing, and deployment of applications within AWS environments. Their suite of services includes consulting, engineering, and automation expertise to implement secure and scalable CI/CD pipelines, facilitating a faster go-to-market strategy for enterprises across various sectors. Stelligent's approach integrates tightly with AWS technologies, offering tools and practices that enhance the cloud capabilities of their customers, ensuring efficient and innovative cloud-based solutions.

Recent Feature Selection for Machine Learning Reviews

Anish Mahesh S.
AS
Anish Mahesh S.Mid-Market (51-1000 emp.)
4.5 out of 5
"Feature selection probably the most daunting task in ML journey"
Feature selection is probably the most daunting task in a ML journey. Especially in an industrial setting there are a plethora of features which ma...
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1 Feature Selection for Machine Learning Reviews

4.5 out of 5
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1 Feature Selection for Machine Learning Reviews
4.5 out of 5
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Anish Mahesh S.
AS
Gasoline Blend Optimization Engineer
Mid-Market(51-1000 emp.)
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What do you like best about Feature Selection for Machine Learning?

Feature selection is probably the most daunting task in a ML journey. Especially in an industrial setting there are a plethora of features which maybe higly co-related to each other thus making the life of an industrial data scientist the most difficult one but alsas there is a solution for this and thats 'Feature Selection for Machine Learning'. Review collected by and hosted on G2.com.

What do you dislike about Feature Selection for Machine Learning?

Making this solution more interpretable and explainable may be a challenge but with further iterations this is always possible. The UI could get a big overhaul too. Review collected by and hosted on G2.com.

What problems is Feature Selection for Machine Learning solving and how is that benefiting you?

Feature selection is always a conundrum for data scientist as there is always one too many faetures which doesn not play any vitalrole for the model output. As they say only a handful of soldiers are enough to wage a war. Review collected by and hosted on G2.com.

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