scikit-learn Reviews & Product Details

sklearn provides consistent interface and the documentation is thorough. It is also highly extensible. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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. Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

Comprehensive collections of ML algorithms and lots of examples and tutorials Review collected by and hosted on G2.com.

Documentation for some functions is rather limited. Not every implemented algorithm is present. Review collected by and hosted on G2.com.

Documentation has great explanation and is very easy to implement. Review collected by and hosted on G2.com.

Very handy for a learner and a professional too. Used it in both the phases without any problems. No dislikes yet! Review collected by and hosted on G2.com.

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 Review collected by and hosted on G2.com.

Sometimes can be tricky to install with the proper dependencies and updates sometimes render old scripts useless Review collected by and hosted on G2.com.

I primarily used it for data processing and very helpful for understanding Artificial Intelligence Review collected by and hosted on G2.com.

for beginners it is quite annoying and dissatisfying, until they understand the concepts. Review collected by and hosted on G2.com.

It include a lot of examples. It is very easy to find something related with your problem. Review collected by and hosted on G2.com.

It does not include convolutional network :( Review collected by and hosted on G2.com.

documentation, easy to use and lots of online support Review collected by and hosted on G2.com.

I feel for some algorithm R has better implementation. Review collected by and hosted on G2.com.

It is well documented and has an experienced community behind it. It also has nearly all the functionality that I would ever need. Review collected by and hosted on G2.com.

It took a little time to get into the python language and build, but this is true with most languages. Review collected by and hosted on G2.com.

User friendly, applies to many modeling algorithms, great documentation, easy to learn Review collected by and hosted on G2.com.

Too Basic visualizations, lack of live interactive dashboard Review collected by and hosted on G2.com.