--- title: scikit-learn Reviews meta_title: 'scikit-learn Reviews 2026: Details, Pricing, & Features | G2' meta_description: Filter 60 reviews by the users' company size, role or industry to find out how scikit-learn works for a business like yours. aggregate_rating: rating_value: 4.8 review_count: 60 scale: '5' date_modified: '2026-08-07' parent_category: name: Artificial Intelligence url: https://www.g2.com/categories/artificial-intelligence --- # scikit-learn Reviews **Vendor:** scikit-learn **Category:** [Machine Learning Software](https://www.g2.com/categories/machine-learning) **Average Rating:** 4.8/5.0 **Total Reviews:** 60 ## About scikit-learn 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. ## scikit-learn Pros & Cons **What users like:** - Users find scikit-learn's **ease of use** beneficial for beginners, simplifying the learning process in machine learning. (1 reviews) - Users appreciate the **clean and intuitive API** of scikit-learn, making it easy for beginners to learn machine learning. (1 reviews) - Users find scikit-learn a **frequently used library** for beginners, thanks to its clean interface and easy access to algorithms. (1 reviews) **What users dislike:** - Users experience **lagging issues** with scikit-learn, especially when modeling complex algorithms, affecting overall performance. (1 reviews) - Users face challenges with **limited customization** in scikit-learn, hindering their ability to tweak algorithms effectively. (1 reviews) - Users find that learning scikit-learn takes a significant amount of time due to its **steep learning curve** for beginners. (1 reviews) ## scikit-learn Reviews ### 1. plug and play machine learning models **Rating:** 4.0/5.0 stars **Reviewed by:** Vikas P. | Associate System Engineer , Small-Business (50 or fewer emp.) **Reviewed Date:** May 28, 2019 **What do you like best about scikit-learn?** I like this library because it is super easy to import the library and use the Machine Learning models. To install scikit-learn it is very easy. They have lots of machine learning models such as random forest, xgboost and many more. You don't need to code from scratch. They provide a lot of parameters to tweak the models also which is helpful. **What do you dislike about scikit-learn?** It is kind of plug and plays but the customization is a little bit hard for the machine learning models. Also, as compared to tensorflow it is slow. **Recommendations to others considering scikit-learn:** If you just need a machine Learning model and don't want any more specification or customization you can go with scikit-learn. It is easy to use and implement. **What problems is scikit-learn solving and how is that benefiting you?** For general machine learning models where I need models and don't want to customize the model, I use scikit-learn prebuild models. ### 2. Incredibly simple, fast, and powerful **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Small-Business (50 or fewer emp.) **Reviewed Date:** July 17, 2019 **What do you like best about scikit-learn?** Scikit-learn is extremely scalable and great for beginners especially. My main experience has been using their support vector classifier, which is ideal for our project in mapping ultrasound imagery to movements of the hand. **What do you dislike about scikit-learn?** Documentation could be a bit better, but other than that it's incredibly reliable and consistent. **What problems is scikit-learn solving and how is that benefiting you?** Enabling amputee musicians to use robotic hands to play music with ultrasound imagery and support vector machines ### 3. Great tool for simple Machine Learning **Rating:** 3.5/5.0 stars **Reviewed by:** Verified User in Education Management | Enterprise (> 1000 emp.) **Reviewed Date:** February 12, 2019 **What do you like best about scikit-learn?** Does offer a wide variety of traditional Machine Learning Algorithms. **What do you dislike about scikit-learn?** Not quite comfortable to use while working on Deep Neural Network. **Recommendations to others considering scikit-learn:** Introduce Deeplearning toolbox **What problems is scikit-learn solving and how is that benefiting you?** Random Forest Algorithm, SVM, Online News Popularity ### 4. I love scikit-learn **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Research | Enterprise (> 1000 emp.) **Reviewed Date:** January 18, 2018 **What do you like best about scikit-learn?** It include a lot of examples. It is very easy to find something related with your problem. **What do you dislike about scikit-learn?** It does not include convolutional network :( **Recommendations to others considering scikit-learn:** look at examples! **What problems is scikit-learn solving and how is that benefiting you?** I am using it for classification and regression problems. ### 5. Useful if not powerful **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Hospital & Health Care | Small-Business (50 or fewer emp.) **Reviewed Date:** October 03, 2017 **What do you like best about scikit-learn?** 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 about scikit-learn?** It took a little time to get into the python language and build, but this is true with most languages. **What problems is scikit-learn solving and how is that benefiting you?** Mostly categorization models, some regression. Seamless with other business processes ### 6. predicting default rates of loans **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Higher Education | Enterprise (> 1000 emp.) **Reviewed Date:** November 09, 2017 **What do you like best about scikit-learn?** User friendly, applies to many modeling algorithms, great documentation, easy to learn **What do you dislike about scikit-learn?** Too Basic visualizations, lack of live interactive dashboard **What problems is scikit-learn solving and how is that benefiting you?** predicting default rates of loans ## scikit-learn Discussions - [What is scikit-learn used for?](https://www.g2.com/discussions/scikit-learn-what-is-scikit-learn-used-for) - 2 comments - [What is Python Scikit learn?](https://www.g2.com/discussions/what-is-python-scikit-learn) - 1 comment - [View scikit-learn pricing details and edition comparison](https://www.g2.com/products/scikit-learn/reviews?filters%5Bnps_score%5D%5B%5D=4§ion=pricing&secure%5Bexpires_at%5D=2026-08-10+16%3A21%3A53+-0500&secure%5Bsession_id%5D=f903b428-eb04-4601-b4bf-13482cbbfb08&secure%5Btoken%5D=73a54eb4461ddae3d330115a4936286b015c9f0f93cba1ab282e89191591194e&format=llm_user) ## scikit-learn Features **Additional Functionality** - Tagging - Natural Language Processing - Data Extraction - Multi-Language - Predictive Analytics - Drag & Drop - Speech Recognition - Reporting/Analytics - Data Storage Management - Virtual Personal Assistant (VPA) - AI Copilot - Customer Segmentation - Collaboration Tools - Data Import/Export - Generative AI - For eCommerce - Role-Based Permissions - Customizable Branding - Search/Filter - Monitoring - Document Management - API - Data Visualization - Trend Analysis - Machine Learning - Access Controls/Permissions - Alerts/Escalation - Performance Metrics - Real-Time Data - Third-Party Integrations - Mobile App - Multiple Data Sources - For Sales Teams/Organizations - Sentiment Analysis - Activity Dashboard - Chatbot - Workflow Automation **Integration - Machine Learning** - Integration - Third-Party Integrations **Learning - Machine Learning** - Training Data - Actionable Insights - Algorithm **Additional Functionality** - Predictive Modeling - Configurable Workflow - Tagging - Data Import/Export - API - Predictive Analytics - Data Visualization - Endpoint Management - Multiple Data Sources - No-Code - Data Preparation - Auditing - Collaboration Tools - Big Data Analytics - ML Algorithm Library - Data Management - Activity Dashboard - Data Capture and Transfer - Activity Tracking - Data Connectors - Data Security - Data Extraction - Reporting & Statistics - Workflow Management - AI Copilot ## Top scikit-learn Alternatives - [MLlib](https://www.g2.com/products/mllib/reviews) - 4.1/5.0 (14 reviews) - [Weka](https://www.g2.com/products/weka/reviews) - 4.3/5.0 (13 reviews) - [Google Cloud TPU](https://www.g2.com/products/google-cloud-tpu/reviews) - 4.5/5.0 (33 reviews)