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scikit-learn

4.9
(28)

Scikit-learn is a software machine learning library for the Python programming language that has a various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.

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scikit-learn review by Vishwas R.
Vishwas R.
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"Machine Learning ToolKit For Python"

What do you like best?

scikit learn basically is the library for python that includes all the machine learning algorithms in it which are perfectly coded to make your work easy.It helps us to look at the application part rather than the implementation part and also reduces our time by eliminating the need of coding the algorithm from scratch.It is a famous and widely used library and also is supported by many open source developers which makes its algorithm very better than any else.Also it has a large variety of dataset which can also be used for testing like iris dataset so it helps a lot during development and testing the code.

What do you dislike?

I actually love this library and spent almost all my worktime using this and have nothing to dislike about it.

Recommendations to others considering the product

I recommend using scikit learn to all the machine learning engineers or other personal of this field to directly implement variety of algorithms in a single line of code.Like suppose if you have to code a SVM for your regression than coding it from scratch might take time but if you use scikit learn you can just call the SVM object and use it to train your data and predict results or use the model accordingly.

What business problems are you solving with the product? What benefits have you realized?

I am a machine learning engineer at innovatee IT solutions which provides machine learning solutions to all the industrial sectors.I have to develop various applications in which we use ML algorithms directly or indirectly and for that implementation I use scikit-learn.It makes my work easy and helps me develop applications which are upto the mark for our clients.

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scikit-learn review by Sunil C.
Sunil C.
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"Best Machine Learning Library For Python"

What do you like best?

Scikit-learn is the most wanted library for python for any machine learning engineer for machine learning project.If you are experienced in ML and have little less knowledge about its implementation then you can use this because here you can create any classifier or regression model just by calling its object.This object can be trained by your training set and this ready trained model can be used to predict the furthur results.The other benefit of it is that if you want to change the parameters of the particular algorithm than also it can be changed by calling the object and passing the necessary values.It also has very clean documentation which is very easy to understand.

What do you dislike?

I have nothing much to dislike about scikit-learn.

Recommendations to others considering the product

I would recommend using scikit-learn if you want to easily implement machine learning models for your company and these models are algorithmic-ally sound because it is the library which is used by many great achiever's in this field so they have also contributed to this library as it is open source.If you are implementing ML related anything in your project in python then go for scikit-learn.

What business problems are you solving with the product? What benefits have you realized?

In my company wherever the word machine learning is conned,at that place scikit learn is being used to implement ML models.I also have been using scikit learn for predicting various stock market results for our consulting company and also have used scikit learn to implement ML related models to any software that our client requires so scikit learn is the integral part of me as far as Machine Learning is concerned.

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scikit-learn review by Yash R.
Yash R.
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"Classic ML library"

What do you like best?

scikit learn is the machine learning library implemented in python.It consists of all the machine learning algorithms like linear regression,logistic regression and many more clustering algorithms preimplemented.You can use such algorithms on your data set by just a single line of code.You can train the model on your data set and use that model to predict furthur values.You can also save your trained model and also change the parameters of the alogrithm to tune the algorithm according to your usage.

What do you dislike?

It is the Classic ML library for python and it has nothing to dislike about it.

Recommendations to others considering the product

I recommend using scikit learn to implement ML algorithms in your software using python because it has range of algorithms implemented in it and you can also tune the parameters of their algorithms according to your requirement.It is far more the best ML library for python and so it is the most recommended library for implementing ML algorithms.

What business problems are you solving with the product? What benefits have you realized?

I use sci-kit learn library to implement various classification and regression algorithms of machine learning in python to furthur integrate those trained models into the software required by the client.It is so simple to use that even a person with beginner knowledge of ML can implement the algorithms with ease.

scikit-learn review by Rahul C.
Rahul C.
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"Machine learning Implementation Python Library"

What do you like best?

It is the python library for implementing machine learning algorithms.It has various algorithms of machine learning preimplemented which you can use just by using single line of code.All the machine learning classifiers are modifyable according to you requirement.You can train your model and save it for your futhur usage and predict results with much ease.It is the best ML library for python you can ever have.

What do you dislike?

Nothing to dislike about the extraordinary Machine learning library.

Recommendations to others considering the product

IT is the best recommended Machine learning library for python.It is very easy to implement ML classifiers on any size of data.Also you can scale the data using scikit learn so it is best ML library for python.If you want to implement ML models to your data with ease,you should use scikit learn.So it is definetly the best library for ML.

What business problems are you solving with the product? What benefits have you realized?

I use Scikit learn for implementing Machine learning in our softwares according to the requirement and data of our clients.It is very useful in the field of data science for implementing various ML classifiers to our data and use it according to our usage.It has made the work of implementing the ML algorithms very easy.

scikit-learn review by Narendra N.
Narendra N.
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"Machine Learning Library For Nascent Developers"

What do you like best?

Scikit learn is a machine learning library for python.You can easily develop and generate Machine Learning models so much easily and also can train the model with just single line of code.It is so easy to implement machine learning algorithm that even nascent developers can easily implement various machine learning model.It can also be used to modify the models variables and build a model according to your usage.

What do you dislike?

It is best ML library available for python so no problems about scikit learn.

Recommendations to others considering the product

I recommend using scikit learn for implementing the ML models easily and without more effort and you can also tune the model according to your requirement and also save the trained model.You will not get anything like this in any other library.If you use python for ML implementation scikit learn is the best framework you can have.

What business problems are you solving with the product? What benefits have you realized?

I use scikit learn to implement and train machine learning models for my websites and also for the softwares that my company develops.I use scikit learn and tune the model of ML according to the project specification and than develop a perfectly trained and tuned model for the software.

scikit-learn review by Jash S.
Jash S.
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"Best Documented ML(Machine Learning) library"

What do you like best?

Scikit learn is the library for machine learning which is well documented that a naive machine learning developer can also use it.The algorithms that are implemented in the library are the common machine learning algorithms and they can scale for almost every size of data.You can easily use the machine learning algorithms in a normal python program and take the advantage of the data analytics through ML using scikit learn.

What do you dislike?

Scikit learn has not left any false clue besides it that is you cannot even find a single evidence for not liking it.

Recommendations to others considering the product

I recommend scikit learn as the best machine learning library for any set of data for implementing various machine learning algorithms.And it is opensource and improvising day by day.

What business problems are you solving with the product? What benefits have you realized?

We use scikit learn for implementing various ML algorithms through python.Using those algorithms we get our data analytics and predictions of stock market.We also provide various solutions through ML algorithms to our clients according to our usage.Recently we built a model for a company for share price prediction for certain of its depending companies.

scikit-learn review by Kartik B.
Kartik B.
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"Best MachineLearning Library"

What do you like best?

The best machine learning library that I have found on the web. It is the library which is used by the experts for machine learning exercises. Using scikit-learn you can easily get your classifier or else regression model developed in a single line and then just train your data through that classifier by passing training data to it and also you can save the trained model and use it in future.You can also customize the famous ML algorithms and tune them according to your usage.

What do you dislike?

Nothing to dislike about the best Machine Learning Library.

Recommendations to others considering the product

Scikit-Learn is the best and guranteed recommended machine learning library for all the machine learning developers over there in the society because you will not find any other library that gives you pre implemented algorithms which you can use by just writing a single line and tuning the algorithm parameters according to your usage

What business problems are you solving with the product? What benefits have you realized?

We use scikit-learn to develop the training model for our as well as other company's usage that require predictive models for their daily usage.We also develop predictive models for our clients as well and give them a working application that is tuned and works according to their requirement so scikit learn is best for us.

scikit-learn review by vivek s.
vivek s.
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"best available machine learning library . "

What do you like best?

Training your data with scikit-learn is very easy . using scikit-learn you can rapidly develop classifier and get your regression models prepared in very less time . the BEST thing about scikit-learn is that you can save your model and your trained data for further use .

What do you dislike?

scikit-learn is a very nice ML library there is nothing to dislike about it .

Recommendations to others considering the product

scikit-learn is a exceptionally robust and versatile Machine Learning library till date . you will not find any replacement for this library .scikit-learn contains all pre-implemented ML algorithms which helps a lot .

What business problems are you solving with the product? What benefits have you realized?

we are developing software based on sentiment analysis and recommender system with the help of scikit-learn . it provides us the in-buit functions and helps us develop the software for the customers rapidly .

scikit-learn review by ishnat s.
ishnat s.
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"A great library for python machine laerning"

What do you like best?

Scikit learn is a great library which all the required modules required for machine learning .It also helps the developer for creating machine on AI and also helps us to train the software. Scikit learn is most advanced library for machine learning used in python because of its vast applications and great user interface and inclusion of different fnctions. And also it can be deployed on different repository platforms like Github.

What do you dislike?

The only thing i dislike about scikit learn is that it demands high computation power due to which it can be used on machines with small number of cores.

Recommendations to others considering the product

i would recommend this library for extensive use of machine learning libraries.

What business problems are you solving with the product? What benefits have you realized?

I have developed a recommend system using scikit learn and it was based on recommending the movies.

scikit-learn review by Nupur M.
Nupur M.
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"Pyhton ML Library with great documentation"

What do you like best?

The best thing I would say is, it is open source. Also the documentation is too good, any newbie can easily learn using scikit-learn with this documentation. Along with the documentation the algorithms they provide are too efficient and fast. Almost all Machine Learning algorithms are provided, so it becomes single and also the best place for a ML enthusiast.

What do you dislike?

Using scikit-learn from all of my Machine Learning tasks, so i would say, 'no dislikes'.

Recommendations to others considering the product

They provide tutorials on their main website: http://scikit-learn.org in every section, I recommend every newbie to go for this tutorials. They have been a great help to me personally.

What business problems are you solving with the product? What benefits have you realized?

I use it for all of my machine learning tasks and for every application I create where ML is used.

scikit-learn review by Paresh A.
Paresh A.
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"Machine Learning API for Python"

What do you like best?

It is a api or a library for python for implementing machine learning algorithms by directly declaring the classifiers and training the data on them.By doing so you can generate a model and then just use that model to predict the values.Scikit learn is opensource library and is contributed by many developers and because of which it has best algorithms which are implemented.Almost all the algorithms can be easily used by single line of code and also the parameters can be modified according to your requirement so it is the best library.

What do you dislike?

I have nothing to dislike about this amazing scikit-learn library.

Recommendations to others considering the product

I recommend using scikit learn to all the software developers and also machine learning developers who would like to implement machine learning algorithms without hassle of hard coding the whole algorithm instead just implement them with a line of code using scikit learn.I also recommend scikit learn because you can also change the parameters of particular algorithms like learning rate according to your requirement so I recommend it for machine learning.

What business problems are you solving with the product? What benefits have you realized?

I am a software engineer and I implement machine learning algorithms for various companies and projects which our clients give us.And when it comes to machine learning I prefer scikit learn because it is the best library with almost all the classifiers and also a huge sized dataset which available with it so it becomes easy to develop common models by just using those dataset so it is a great library for us.

scikit-learn review by G2 Crowd User in Telecommunications
G2 Crowd User in Telecommunications
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"Great Python library for machine learning"

What do you like best?

Scikit-learn is a well-documented Python library that gives easy access to many prominent machine learning algorithms. The library is designed in such a way as to have a consistent API regardless of which algorithm you choose to use, so it is easy to pick up and try a new algorithm you have never used before.

What do you dislike?

As with any library of this type (compilation of many different algorithms), it doesn't always contain the content you're looking for. Scikit-learn only contains the most popular algorithms, so if you're looking for an implementation of a more specialized algorithm, it's very possible you won't find it in the library.

Recommendations to others considering the product

Make sure to read through documentation in depth. API is intuitive but requires understanding of how machine learning algorithms work on a high level. Most basic and common data transformation and manipulation tools are already built-in, so try to use those unless your data set requires something more specialized.

What business problems are you solving with the product? What benefits have you realized?

I use scikit-learn to access unsupervised learning algorithms to cluster rows of data to join datasets with no pre-existing defined relationships. This has lead to product categorization on a lower level than has ever been available up until now due to the nature of my company's data.

scikit-learn review by Rahul S.
Rahul S.
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"The most reliable and efficient machine learning library"

What do you like best?

Most of the complex problems are solved easily with the help of it's potential of selecting algorithms. It also covers most of the machine learning tasks. It has a great interface and is a well-updated module. The scalability and robustness makes it very easy to use.

What do you dislike?

It is not very likely used where there is a high requirement of statistical information.

Recommendations to others considering the product

Recommending scikit-learn to others would be a great pleasure for me. It's quality of support and above that a well-documented API makes it one of the best machine learning library till now.

What business problems are you solving with the product? What benefits have you realized?

Image processing. Face as well as Handwriting recognition. Also in generating multi-label datasets.

scikit-learn review by Sunny S.
Sunny S.
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"One of the best machine learning library for Python programming language"

What do you like best?

It covers most of the machine learning tasks. It scales to most data problems. The selection of solid algorithms. A well-updated module. It's API documentation. The support for customer. It is robust and easy to use.

What do you dislike?

It doesn't support GPU acceleration. It has less of a focus on statistics than R does.

Recommendations to others considering the product

I would definitely recommend to use scikit-learn as it has a well-documented API and is also easy to use. It is best suited for implementing most of the machine learning tasks. It has a great customer support.

What business problems are you solving with the product? What benefits have you realized?

Audio,Text and Image categorization. Bio-informatics. Multi-label classification and Multi-class classification problems. Loading and Generating multi-label datasets.

scikit-learn review by Jeel L.
Jeel L.
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"Very well documented ML library for Python"

What do you like best?

The documentation is clean and clear one can easily understand. If you face any problems you can easily find the solution over the internet as there are a lot of people using it around the world. I almost use is everywhere I use Machine Learning.

What do you dislike?

No dislikes for such a well documented and helpful library.

Recommendations to others considering the product

There are lot of tutorials available over the internet but I personally recommend this YouTube channel: https://www.youtube.com/user/sentdex to start with scikit-learn.

What business problems are you solving with the product? What benefits have you realized?

Of all the ML projects we work at Techy Developers, we use scikit-learn as ML library. It works as a charm, has produced great results every time used.

scikit-learn review by Riya T.
Riya T.
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"Open Source Machine Learning Library"

What do you like best?

- It is open source.

- It has a huge community support.

- One can easily find tutorials to learn it.

- Detailed documentation with details.

What do you dislike?

It has been my helping hand when it comes to Machine Learning. I have no problem or dislikes for this very great and helpful library.

Recommendations to others considering the product

Refer documentation for any help, they have provided in detail explanation of every algorithm with example. I also recommend to refer tutorials of sentdex on YouTube.

What business problems are you solving with the product? What benefits have you realized?

Using it to build Machine Learning based projects.

scikit-learn review by G2 Crowd User in Information Technology and Services
G2 Crowd User in Information Technology and Services
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"Machine learning in Python"

What do you like best?

It has all the tools to structure the machine learning problem efficiently and effectively. It has all kind of algorithms - supervised: linear regression, logistic regression, decision trees, random forest, gbm etc , unsupervised: kmeans, dbscans, spectral clustering, optics etc, and dimensionality reduction algorithms . An exhaustive list of clustering algorithms is implemented. It is possible to automate end-to-end model building workflow such as model building, comparison, selection using cross-validation or other approaches, storing the object for scoring or returning the prediction on unseen datasets.

Documentations is very well written - it not only explains the function definition but gives a good background of underlying mathematics used in algorithms.

What do you dislike?

Their deep learning framework is not as exhaustive as the other open source available software specific for it, but we are not missing out on these features as other open source projects are good alternate options. So one might have to experiment outside scikit if they want to explore more advanced neural network algorithms

Recommendations to others considering the product

It is a very solid tool for machine learning, if you are looking for unsupervised algorithms - it has an exhaustive list of algorithms to support your analysis and model workflows.

What business problems are you solving with the product? What benefits have you realized?

We are building predictive propensity models for customers to buy particular services using scikit-learn, and also use it for data preprocessing for deep learning applications.

scikit-learn review by Rishab G.
Rishab G.
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"Implement ML Algorithms in just few lines of code "

What do you like best?

Documentation has great explanation and is very easy to implement.

What do you dislike?

Very handy for a learner and a professional too. Used it in both the phases without any problems. No dislikes yet!

Recommendations to others considering the product

Read the documentation it contains simple and easy steps to implement.

What business problems are you solving with the product? What benefits have you realized?

Made products that use Machine Learning algorithms using scikit-learn. Used for simple as well as complex products that involve ML in it.

scikit-learn review by G2 Crowd User in Hospital & Health Care
G2 Crowd User in Hospital & Health Care
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"Ease of use"

What do you like best?

sklearn provides consistent interface and the documentation is thorough. It is also highly extensible.

What do you dislike?

I would prefer that cross_val_score provides a mechanism for out of sample evaluation. Assuming your sample is rebalanced, you may want the nth fold used for evaluation to be an unbalanced, out of sample dataset so as to the true performance of your model in the wild. cross_val_score does not provide this functionality. The pipeline class should also provide a mechanism to chain very many transformations and allow a grid search of best parameters across all the transformations. This is particularly useful in NLP pipeline where you stemming, removing stop words, ngram-ing, etc. could be a separate transformation and you want to know which transformation and parameters (e.g. the n in ngram) produced the best result.

What business problems are you solving with the product? What benefits have you realized?

Predicting hospital readmissions.

scikit-learn review by G2 Crowd User in Higher Education
G2 Crowd User in Higher Education
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"Great machine learning library for Python"

What do you like best?

Comprehensive collections of ML algorithms and lots of examples and tutorials

What do you dislike?

Documentation for some functions is rather limited. Not every implemented algorithm is present.

Recommendations to others considering the product

Great library to do machine learning in Python, check out tutorials for each module before using it as it usually has lots of useful examples.

What business problems are you solving with the product? What benefits have you realized?

Unsupervised clustering and classification. On their website, they have a collection of examples and tutorials that can be easily followed.

scikit-learn review by G2 Crowd User in Higher Education
G2 Crowd User in Higher Education
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"Scikit-learn is really awesome package included in python"

What do you like best?

You can do classification, clustering, regression, pre processing and so many. If you are working in machine learning based research, I would highly recommend this package.

What do you dislike?

Nothing is dislike. Every thing comes without cost and its really efficient. You just need to know basic python coding

What business problems are you solving with the product? What benefits have you realized?

I am using it in my research work related to signal processing nd machine learning.

scikit-learn review by G2 Crowd User in Higher Education
G2 Crowd User in Higher Education
Validated Reviewer
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"Great ML package!"

What do you like best?

Scikit learn is a great package for machine learning in python. It contains most popular ML algorithms and provides extensive documentation with examples so even those with minimal programming background can implement the algorithms

What do you dislike?

Sometimes can be tricky to install with the proper dependencies and updates sometimes render old scripts useless

Recommendations to others considering the product

Great for out of the box implementation of popular ML algorithms

What business problems are you solving with the product? What benefits have you realized?

Most of my research is modeling/prediction based so I use scikit frequently. The benefits are it’s very easy to implement

scikit-learn review by Snehal M.
Snehal M.
Validated Reviewer
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"Brilliant Software for learning AI & ML"

What do you like best?

I primarily used it for data processing and very helpful for understanding Artificial Intelligence

What do you dislike?

for beginners it is quite annoying and dissatisfying, until they understand the concepts.

What business problems are you solving with the product? What benefits have you realized?

Data Processing, data modelling

scikit-learn review by G2 Crowd User in Hospital & Health Care
G2 Crowd User in Hospital & Health Care
Validated Reviewer
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"Scikit learn is good"

What do you like best?

It has the best libraries that can run on data. It is mainly helpful when you are doing supervised or unsupervised machine learning on your data

What do you dislike?

python is slow. Therefore using the libraries makes dataanalysis slow.

Recommendations to others considering the product

Scikit learn is amazing , It has a lot of features for machine learning.

What business problems are you solving with the product? What benefits have you realized?

credit risk analysis, Direct libraries available for many machine learning alogorithms

scikit-learn review by G2 Crowd User in Financial Services
G2 Crowd User in Financial Services
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Verified Current User
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"5 years of building machine learning models"

What do you like best?

documentation, easy to use and lots of online support

What do you dislike?

I feel for some algorithm R has better implementation.

What business problems are you solving with the product? What benefits have you realized?

fraud prediction

scikit-learn review by G2 Crowd User in Hospital & Health Care
G2 Crowd User in Hospital & Health Care
Validated Reviewer
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"Useful if not powerful"

What do you like best?

It is well documented and has an experienced community behind it. It also has nearly all the functionality that I would ever need.

What do you dislike?

It took a little time to get into the python language and build, but this is true with most languages.

What business problems are you solving with the product? What benefits have you realized?

Mostly categorization models, some regression. Seamless with other business processes

scikit-learn review by G2 Crowd User in Higher Education
G2 Crowd User in Higher Education
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"I love scikit-learn"

What do you like best?

It include a lot of examples. It is very easy to find something related with your problem.

What do you dislike?

It does not include convolutional network :(

Recommendations to others considering the product

look at examples!

What business problems are you solving with the product? What benefits have you realized?

I am using it for classification and regression problems.

scikit-learn review by G2 Crowd User in Information Technology and Services
G2 Crowd User in Information Technology and Services
Validated Reviewer
Review Source

"predicting default rates of loans"

What do you like best?

User friendly, applies to many modeling algorithms, great documentation, easy to learn

What do you dislike?

Too Basic visualizations, lack of live interactive dashboard

What business problems are you solving with the product? What benefits have you realized?

predicting default rates of loans

Kate from G2 Crowd

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