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scikit-learn Review

scikit-learn
Our score: 8.9 User satisfaction: 100%

What is scikit-learn?

scikit-learn is a free-to-use machine learning module for Python built on SciPy. It is a straightforward and effective tool for data mining and data analysis. Because it is released with a BSD license, it can be used for both personal and commercial reasons.

With scikit-learn, users are able to conduct a variety of tasks under different categories like model selection, clustering, preprocessing, and more. The module provides the means to complete implementations.

Moreover, scikit-learn has an extensive use. It is being utilized by big companies in different industries like music streaming, hotel bookings, and more. This means that users can integrate algorithms in the platform to their own applications.

Overview of scikit-learn Benefits

Free Platform

Because scikit-learn is released with a BSD license, it can be used for free by everyone. This license has minimal restrictions; therefore, users can utilize it to design their applications and platforms with little worry over limitations.

Industrial Use

scikit-learn is a helpful platform that can predict consumer behavior, identify abusive actions in the cloud, create neuroimages, and more. It is being used extensively by commercial and research organizations around the world, a testament to its ease of use and overall advantage.

Collaborative Library

scikit-learn began as a one-man mission but now it is being built by numerous authors from INRIA spearheaded by Fabian Pedregosa and individual contributors who are not attached to teams or organizations. This makes the module a well-updated one, releasing updates several times a year. Users can also look forward to assistance from an international community, in case they have queries or if they hit snags in development using the module.

Ease of Use

Commercial entities and research organizations alike have employed scikit-learn in their processes. They all agree that the module is easy-to-use, thereby allowing them to perform a multitude of processes with nary a problem.

API Documentation

scikit-learn ensures that users old and new alike get the assistance they need in integrating the machine learning module into their own platforms. That is why a documentation detailing the use of its API exists that users can access anytime on the website. This makes certain developers can implement machine learning algorithms offered by the tool seamlessly.

Overview of scikit-learn Features

  • Classification
  • Regression
  • Dimensionality Reduction
  • Model Selection
  • Clustering
  • Preprocessing

scikit-learn Position In Our Categories

Since companies have unique business requirements, it is logical they abstain from seeking a one-size-fits-all, “perfect” software solution. Still, it is almost impossible to pinpoint such application even among recognizable software products. The best thing to undertake would be to make a list of the several main aspects that need careful thought like crucial features, pricing, technical skill competence of the users, organizational size, etc. After which, you should double down on your research through and through. Read some of these scikit-learn evaluations and check out the other software systems in your shortlist in detail. Such detailed product research ensure you take out mismatched software products and buy the system which offers all the benefits your business requires.

Position of scikit-learn in our main categories:

TOP 10

scikit-learn is one of the top 10 Artificial Intelligence Software products

If you are considering scikit-learn it might also be a good idea to analyze other subcategories of Artificial Intelligence Software collected in our base of B2B software reviews.

Organizations have diverse wants and requirements and no software application can be perfect in such a scenario. It is useless to try to find an ideal out-of-the-box software system that meets all your business wants. The intelligent thing to do would be to modify the system for your unique wants, employee skill levels, finances, and other aspects. For these reasons, do not hasten and invest in well-publicized leading solutions. Though these may be widely used, they may not be the best fit for your particular needs. Do your groundwork, check out each short-listed application in detail, read a few scikit-learn Artificial Intelligence Software reviews, call the seller for clarifications, and finally select the app that presents what you want.

How Much Does scikit-learn Cost?

scikit-learn Pricing Plans:

Free Trial

scikit-learn

Free

scikit-learn has no enterprise pricing plan. Instead, it is a free-to-use software covered by the BSD license.

User Satisfaction

Positive Social Media Mentions 195
Negative Social Media Mentions 0

We realize that when you make a decision to buy Artificial Intelligence Software it’s important not only to see how experts evaluate it in their reviews, but also to find out if the real people and companies that buy it are actually satisfied with the product. That’s why we’ve created our behavior-based Customer Satisfaction Algorithm™ that gathers customer reviews, comments and scikit-learn reviews across a wide range of social media sites. The data is then presented in an easy to digest form showing how many people had positive and negative experience with scikit-learn. With that information at hand you should be equipped to make an informed buying decision that you won’t regret.

Technical details

Devices Supported

  • Windows
  • Linux
  • Mac

Deployment

  • On Premise
  • Open API

Language Support

  • English

Pricing Model

  • Free

Customer Types

  • Small Business
  • Large Enterprises
  • Medium Business
  • Freelancers

What Support Does This Vendor Offer?

  • email
  • phone
  • live support
  • training
  • tickets

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scikit-learn Comparisons

scikit-learn user reviews

Scikit-learn is your classic machine learning library

Read full review >
Mariane
5/5

Overall impression

4/5

Customer Support

5/5

Value for Money

4/5

Ease of Use

Published on: 03.12.2019 Company Size: More than 100 Employees Industry: Computer Software

Scikit-learn Review

Read full review >
Aric
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

4/5

Ease of Use

Published on: 30.11.2019 Company Size: Industry: Computer Software

Great Machine Learning Library for Python

Read full review >
Eloy
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

4/5

Ease of Use

Published on: 29.11.2019 Company Size: More than 100 Employees Industry: Higher Education

A must-have machine learning library

Read full review >
Kallie
5/5

Overall impression

5/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 18.11.2019 Company Size: More than 100 Employees Industry: Internet

An awesome library that contains many ML models you can plug and play

Read full review >
Weldon
4/5

Overall impression

3/5

Customer Support

3/5

Value for Money

4/5

Ease of Use

Published on: 14.11.2019 Company Size: More than 100 Employees Industry: Information Technology and Services

What are scikit-learn pricing details?

scikit-learn Pricing Plans:

Free Trial

scikit-learn

Free

scikit-learn has no enterprise pricing plan. Instead, it is a free-to-use software covered by the BSD license.

What integrations are available for scikit-learn?

scikit-learn provides documentation for the use of its API if you want to integrate your app. No other integration information is provided.

scikit-learn average rating:

Average score
4.8/5 (17 user reviews)
5/5

Overall impression

5/5

Customer Support

4/5

Value for Money

4/5

Ease of Use

Write your own review of this product

ADD A REVIEW

The most favorable review

Aric

PROS: It contains a wide range of perfectly coded machine learning algorithms which makes it easier to accomplish ML related tasks. No need to code the algorithm from scratch so we are able to save a lot of time. Users can focus on the application itself and worry less about the implementation. Also, it offers a huge variety of dataset which can be utilized for testing. Scikit-learn has so much to offer. So it's not surprising that many open source developers are supporting it and a lot of individuals have been using this library.

CONS: Nothing. I definitely love this library. In fact, I usually spend almost all my working hours using this.

Reviewed 3 months ago

Read full review >

The least favorable review

Jessyca

PROS: With lots of tools it has to offer, it's possible to use this solution to develop an end-to-end machine learning platform. It has a plethora of machine learning algorithms like decision tree, logistic regression, support vector machines, linear discriminant analysis, and other clustering algorithms as well as boosting algorithms. There are also available pre-processing tools as well as hyperparameter tuning tools including GrindSearchCV and RandomSearchCV. It also offers different metric types to tune the model for precision, accuracy, etc. On top of that, this software works well with motplotlib, pandas, and other Python libraries.

CONS: It doesn't contain more advanced algoritms like LightGBM, XGBoost, and Catboost. Also, hyperparameter tuning is quite time consuming. Facilitating GPU may solve this problem.

Reviewed 5 months ago

Read full review >

More reviews from 17 actual users:

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  • Most negative

Scikit-learn is your classic machine learning library

Read full review >
Mariane
5/5

Overall impression

4/5

Customer Support

5/5

Value for Money

4/5

Ease of Use

Published on: 03.12.2019 Company Size: More than 100 Employees Industry: Computer Software

PROS: I can access a wide range of machine learning algorithms such as logistic regression, linear regression, etc. and use them on our dataset through a single line of code. I train the model on our dataset and utilize that model to foresee further values. It also allows me to change the algorithm’s parameters according to the usage and save the trained model.

CONS: I don’t see any drawback. Scikit-learn is just your classic machine learning library for Python.

What do you think about this review? Great Poor

Scikit-learn Review

Read full review >
Aric
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

4/5

Ease of Use

Published on: 30.11.2019 Company Size: Industry: Computer Software

PROS: It contains a wide range of perfectly coded machine learning algorithms which makes it easier to accomplish ML related tasks. No need to code the algorithm from scratch so we are able to save a lot of time. Users can focus on the application itself and worry less about the implementation. Also, it offers a huge variety of dataset which can be utilized for testing. Scikit-learn has so much to offer. So it's not surprising that many open source developers are supporting it and a lot of individuals have been using this library.

CONS: Nothing. I definitely love this library. In fact, I usually spend almost all my working hours using this.

What do you think about this review? Great Poor

Great Machine Learning Library for Python

Read full review >
Eloy
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

4/5

Ease of Use

Published on: 29.11.2019 Company Size: More than 100 Employees Industry: Higher Education

PROS: I can use this to do a lot of things like pre processing, regression, clustering and classification. If you are working on ML based research, I suggest you give this a try. I promise it's worth it.

CONS: No cons. I find this package really amazing, reliable, and efficient. You'll just need basic Python coding knowledge to be able to maximize its value.

What do you think about this review? Great Poor

A must-have machine learning library

Read full review >
Kallie
5/5

Overall impression

5/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 18.11.2019 Company Size: More than 100 Employees Industry: Internet

PROS: I’m a satisfied user of this tool for many years now and I think the best thing about it is that it makes it easier to implement and use machine learning algorithms. I started using this tool when I was still a student and I am still using it until now. It helps me complete ML tasks faster. Another thing, scikit-learn is becoming better and better and its algorithms remain up-to-date.

CONS: Scikit-learn is a decent library and through the years of using it, I still haven’t seen any disadvantage.

What do you think about this review? Great Poor

An awesome library that contains many ML models you can plug and play

Read full review >
Weldon
4/5

Overall impression

3/5

Customer Support

3/5

Value for Money

4/5

Ease of Use

Published on: 14.11.2019 Company Size: More than 100 Employees Industry: Information Technology and Services

PROS: Software installation is pretty easy. Importing the library and using the ML models is also a breeze. But the best thing is, it offers so many ML learning models we can use including xgboost and random forest. The models can be modified, which is really helpful. Also, we don’t have to code from scratch, which saves us a significant amount of time.

CONS: It is slow compared to tensorflow. Also, modifying the machine learning models can be pretty challenging.

What do you think about this review? Great Poor

The best machine learning library we’ve found in the market today

Read full review >
Nichole
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 13.11.2019 Company Size: Industry: Computer & Network Security

PROS: We're able to train data easily, and develop classifier and prepare regression models faster. But I think the best thing about using scikit-learn is the ability to save our model and trained data for future references.

CONS: Nothing. This machine learning library is generally awesome.

What do you think about this review? Great Poor

Provides reliable prediction of consumer behaviour for an app

Read full review >
Amina
5/5

Overall impression

4/5

Customer Support

5/5

Value for Money

5/5

Ease of Use

Published on: 22.10.2019 Company Size: Industry: N/A

PROS: It’s our go-to-tool for most of our standard machine learning tasks such as regression, dimensionality reduction, clustering, classification, etc. It’s efficient and great for beginners.

CONS: Statistics is lacking. It would be nice if they give more focus on this. For instance, provide more details about regression. Some of scikit-learn competitors do better in this aspect.

What do you think about this review? Great Poor

Scikit-learn Feedback

Read full review >
Sarina
5/5

Overall impression

5/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 16.10.2019 Company Size: More than 100 Employees Industry: Information Technology and Services

PROS: scikit-learn is by far the best open source machine learning library for Python in the market today. It is simple yet powerful. We are able to access almost all ML algorithms and everything is perfectly coded so we don't have to. The algorithms can be used easily through a single line of code. The parameters can be customized according to your requirements. You can generate models with ease and use them to predict values.

CONS: None. Scikit-learn is an amazing library.

What do you think about this review? Great Poor

Scikit-learn Feedback

Read full review >
Bertram
5/5

Overall impression

5/5

Customer Support

5/5

Value for Money

4/5

Ease of Use

Published on: 04.10.2019 Company Size: More than 100 Employees Industry: Information Technology and Services

PROS: Perfect for those with experience in machine learning but have little knowledge about the implementation. It allows users to make any regression or classifier model by simply calling its object and use the training set to train the object. Afterwards, the ready-trained model will be capable of predicting further results. Modifying the parameters of a certain algorithm is also simple. Just call the object and pass the needed values. Lastly, scikit-learn got a nice documentation that you can understand easily.

CONS: I believe using this library brings no disadvantage.

What do you think about this review? Great Poor

A machine learning library that we can rely on

Read full review >
Lilyan
5/5

Overall impression

5/5

Customer Support

5/5

Value for Money

4/5

Ease of Use

Published on: 27.09.2019 Company Size: Industry: Computer Software

PROS: Its interface is great and the module is up-to-date. It got many different algorithms which makes it easier to solve complicated problems. Overall, the platform is easy to use, scalable and robust.

CONS: If there is a high need for stat information, it cannot be likely used.

What do you think about this review? Great Poor

An awesome solution!

Read full review >
Marietta
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 22.09.2019 Company Size: More than 100 Employees Industry: Internet

PROS: It lets you train the ML models and gives nice and easy-to-understand documentations. Getting started with Machine Learning can be quite scary and overwhelming but scikit-learn makes things easier and simpler.

CONS: I’ve been using scikit-learn for a while now and everything is still great and working perfectly. No drawback.

What do you think about this review? Great Poor

So far the best solution we’ve ever used for machine learning

Read full review >
Jessyca
4/5

Overall impression

4/5

Customer Support

3/5

Value for Money

4/5

Ease of Use

Published on: 17.09.2019 Company Size: More than 100 Employees Industry: N/A

PROS: With lots of tools it has to offer, it's possible to use this solution to develop an end-to-end machine learning platform. It has a plethora of machine learning algorithms like decision tree, logistic regression, support vector machines, linear discriminant analysis, and other clustering algorithms as well as boosting algorithms. There are also available pre-processing tools as well as hyperparameter tuning tools including GrindSearchCV and RandomSearchCV. It also offers different metric types to tune the model for precision, accuracy, etc. On top of that, this software works well with motplotlib, pandas, and other Python libraries.

CONS: It doesn't contain more advanced algoritms like LightGBM, XGBoost, and Catboost. Also, hyperparameter tuning is quite time consuming. Facilitating GPU may solve this problem.

What do you think about this review? Great Poor

Powerful yet simple deep learning api and machine learning library for python

Read full review >
Antonette
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

4/5

Ease of Use

Published on: 13.09.2019 Company Size: More than 100 Employees Industry: Information Technology and Services

PROS: It is easy to create and run ML algorithm for any model. Whenever I need to utilize a linear regression model, I simply call its object, train my data on it, and predict when needed. Whenever I need a KNN for face recognition I simply call its KNN classifier with the right hyper parameters and utilize it in the face recognition model. It’s very simple. There are also several custom datasets available which can be easily imported and used. Overall, simplicity is the best thing about this tool.

CONS: I haven’t found any cons yet. Scikit-learn is a great library.

What do you think about this review? Great Poor

A powerful, fast, and straightforward tool

Read full review >
Baby
4/5

Overall impression

3/5

Customer Support

3/5

Value for Money

4/5

Ease of Use

Published on: 11.09.2019 Company Size: Industry: Computer Software

PROS: We use its support vector classifier in mapping ultrasound imagery to hand movements and it works fairly well. Generally, the platform is very simple which makes it ideal for begginners but it is also extremely scalable so you can use it to do more tasks.

CONS: Poor documentation but other than that scikit-learn is very consistent and reliable.

What do you think about this review? Great Poor

Excellent documentation

Read full review >
Mac
5/5

Overall impression

4/5

Customer Support

5/5

Value for Money

4/5

Ease of Use

Published on: 08.09.2019 Company Size: Industry: Computer Software

PROS: Almost all machine learning algorithms are available in this library. Its documentation is pretty fast, efficient, and great for beginners. Lastly, it is open source. If you are new in machine learning or just looking for a great ML library for Python, I highly recommend this one.

CONS: I use scikit-learn for all my machine learning tasks and by far it is efficient and I haven't encountered any serious concern yet (hopefully, I won't)

What do you think about this review? Great Poor

The best ML library for Phyton

Read full review >
Queenie
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 05.09.2019 Company Size: More than 100 Employees Industry: N/A

PROS: I think its the simplicity that makes scikit-learn awesome and different from other machine learning frameworks. It offers incredible one line function calls to complicated functions. The documentation is nice and human readable that even a begginner would be able to easily understand it. The best thing is, scikit-learn offers libraries for data reprocessing which means you can do a lot of things with it.

CONS: Data should be in a particular format in order to train models. Also, the process is pretty time consuming. And there are times when an error message does not give much insight into what has gone wrong ,which can be really stressful.

What do you think about this review? Great Poor

It has made Machine Learning a breeze

Read full review >
Krista
5/5

Overall impression

4/5

Customer Support

4/5

Value for Money

5/5

Ease of Use

Published on: 03.09.2019 Company Size: 1-10 Employees Industry: Computer Hardware

PROS: It offers a number of different machine learning algorithms, eliminating the need to build one from scratch. There's also the ability to split the provided dataset into train as well as validation data through passing split ratio. Lastly, it can be integrated with other deep learning frameworks.

CONS: I haven't found any cons of using scikit-learn. It's great and has helped me accomplish many things in machine learning.

What do you think about this review? Great Poor
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Reviewed By Louie Andre
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