# python-recsys Reviews **Vendor:** BLLIP Parser **Category:** [Machine Learning Software](https://www.g2.com/categories/machine-learning) **Average Rating:** 4.5/5.0 **Total Reviews:** 14 ## About python-recsys python-recsys is a python library for implementing a recommender system. ## python-recsys Reviews ### 1. An easier way to work with data **Rating:** 4.5/5.0 stars **Reviewed by:** Luis M. | data analyst, Enterprise (> 1000 emp.) **Reviewed Date:** June 17, 2021 **What do you like best about python-recsys?** I like the capacity of the tool to work with a large quantity of data **What do you dislike about python-recsys?** I'm not too fond of the interface. It is not very attractive to work with **What problems is python-recsys solving and how is that benefiting you?** With python I'm able to work faster in my diary activities ### 2. Very helpful and easy to use **Rating:** 4.5/5.0 stars **Reviewed by:** Caroline M. | Software QA Tester, Small-Business (50 or fewer emp.) **Reviewed Date:** April 21, 2020 **What do you like best about python-recsys?** It's an open-source rep that allow the user to install easily. the coding experience is very helpful and easy **What do you dislike about python-recsys?** Nothing to say about dislike. The rep is very helpful for anyone **Recommendations to others considering python-recsys:** Start to use right now, its everything more easier **What problems is python-recsys solving and how is that benefiting you?** I'm learning to automate tests, because I work with manual tests. ### 3. A good toolkit for implementing a complex recommender system **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** January 31, 2019 **What do you like best about python-recsys?** Python-recsys is a powerful python library that consist in a implementation of a recommeder system. You can recommend an item providing a user-based o item-based mechanism. Some matrix decomposition algorithms are implemented, such as singular value decomposition, and you can evaluate results through standard performance measures, in order to find best tuning params for your specific domain. Algorithms are supported with a great documentation and a lot of datasets to experiment. **What do you dislike about python-recsys?** Python-recsys doesn't work with python 3, so if you have legacy projects in python 2, you cannot integrate it. Some well known algorithms are not implemented and is not possibile to add variants to implemented ones The lib users community is not very large, so don't expect to have a lot of interactions if you have some problems in using the library. **Recommendations to others considering python-recsys:** Keep attention to python version. For using this lib you have to study some technicalities in recommender systems and intelligent systems. **What problems is python-recsys solving and how is that benefiting you?** I've implemented a sophisticated recommender system to recommend e-commerce item in a cotext-aware environment. It was very simply, with some knowledge of theory paradigm in recommeder systems and personalized intelligent systems. ### 4. python-recsys open-source **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Design | Mid-Market (51-1000 emp.) **Reviewed Date:** March 19, 2019 **What do you like best about python-recsys?** Python-recsys is open source platform and current trend is open source technology. and its provide to best Library in different different functionality based. **What do you dislike about python-recsys?** Python Bug Tracker services are not god in my side. its my own experience. sorry for not all side dislike in Bug Tracker . but my side some issues .. **Recommendations to others considering python-recsys:** python-recsys its very help fool language providers. i fully support Recommendations.+++ **What problems is python-recsys solving and how is that benefiting you?** Python is a mature language for programming. so i need to many client want best programing and secure langues that time i use Recsys services and i get best benefits. an my la client are happy ### 5. Recommended **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Program Development | Small-Business (50 or fewer emp.) **Reviewed Date:** March 19, 2019 **What do you like best about python-recsys?** Makes it easier with handling of datasets and is quite easy to implement. There is a learning curve but you can get over that quite easily. **What do you dislike about python-recsys?** It is a new origins library and the searching algorithim doesn't always work for what you'll need. It still seems a bit new and undeveloped but time will tell. **Recommendations to others considering python-recsys:** It is good for an e commerce item and we can see a good use of it in the future. **What problems is python-recsys solving and how is that benefiting you?** It is useful for analyzing CC data. I think that you can implement and use it for a host of different tasks as well. ### 6. Fairly easy to pick up **Rating:** 4.0/5.0 stars **Reviewed by:** Jay B. | Engineering Intern, Computer Software, Enterprise (> 1000 emp.) **Reviewed Date:** January 21, 2019 **What do you like best about python-recsys?** The Python-recsys library is great once you get past the bland documentation. It makes great usage of Numpy and Scipy to offer an incredibly accurate recommender system. **What do you dislike about python-recsys?** It is 2019 and there is still no support for python 3, unfortunately. This was ultimately the reason why we did not implement it into our environment after testing. **Recommendations to others considering python-recsys:** This is your go-to if you do not require Python 3 support. **What problems is python-recsys solving and how is that benefiting you?** This library can be used to create a recommender system that makes sound predictions based on user behavior. ### 7. A great decision recommendation Library **Rating:** 4.0/5.0 stars **Reviewed by:** Verified User in Facilities Services | Mid-Market (51-1000 emp.) **Reviewed Date:** March 19, 2019 **What do you like best about python-recsys?** In the models ive used, the hybrid model is great for having accurate predictive output and recommendations. **What do you dislike about python-recsys?** There can be some issues that arise when dealing with very big data. **What problems is python-recsys solving and how is that benefiting you?** Recsys uses a SVD model which is beneficial for sparse matrix, you can use hybrid filtering and there is a lot of support for this library. ### 8. Python we are using with github purpose, its very compatiable **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Enterprise (> 1000 emp.) **Reviewed Date:** March 19, 2019 **What do you like best about python-recsys?** We used Python for our automation deployment tool & its so nice fast in processing while comparing to other things. Compatibility wise, scalability & performance. Coding, execution-wise it's so simple & easy to do. **What do you dislike about python-recsys?** Nothing to say anything wrong about this. its quite easy to use any kind of tools & compatible with all. **Recommendations to others considering python-recsys:** It's good to use for any kind of integration tool to use in the runtime environment. **What problems is python-recsys solving and how is that benefiting you?** for our automation tools which we are using for an intergration purpose, it's so simple to execute with the help of Python. ### 9. Quite Innovative **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Information Technology and Services | Mid-Market (51-1000 emp.) **Reviewed Date:** March 19, 2019 **What do you like best about python-recsys?** The library does really well what its supposed to do with recommendation system, specifically in our implementation of retail sites **What do you dislike about python-recsys?** There are workarounds to some things but there are some core features missing like missing frequently viewed recommendations, etc. **Recommendations to others considering python-recsys:** It is useful for certain applications and have to put some workaround for others. **What problems is python-recsys solving and how is that benefiting you?** Recommendation system for a internal retail project for a client ### 10. Software **Rating:** 4.5/5.0 stars **Reviewed by:** Sama S. | COO, Small-Business (50 or fewer emp.) **Reviewed Date:** March 19, 2019 **What do you like best about python-recsys?** Its a great technical software. Not easy to use without experience. **What do you dislike about python-recsys?** Highly technical, great for the people with experience. **What problems is python-recsys solving and how is that benefiting you?** used heavily on evaluations. ### 11. Great ability to customize **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Transportation/Trucking/Railroad | Enterprise (> 1000 emp.) **Reviewed Date:** March 20, 2019 **What do you like best about python-recsys?** If you are comfortable with Python, using this for recommendation engines will be easy. Accommodates a variety of algorithm types including classification recommendations, popularity based and recall. **What do you dislike about python-recsys?** Tedious to install updated systems . Some libraries don't work on certain systems **What problems is python-recsys solving and how is that benefiting you?** Web page/service implementation and advanced market data analytics/research ### 12. Has everything for your programming needs **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Accounting | Mid-Market (51-1000 emp.) **Reviewed Date:** November 01, 2018 **What do you like best about python-recsys?** Includes a big library in order for you to be able to implement what you need in your algorithm, makes good use for what you need to complete your task at hand. Techniques are very developed. **What do you dislike about python-recsys?** This software is not available for one of the newer python. **Recommendations to others considering python-recsys:** If you know how to use python, then use this to further advance your algorithm. Get the opportunity to analyze your data even better for better work flow. **What problems is python-recsys solving and how is that benefiting you?** Being able to organize data and offer solutions. ### 13. python-recsys Library for Recommender Systems **Rating:** 4.5/5.0 stars **Reviewed by:** Anastasia A. | Analista de sistema, Small-Business (50 or fewer emp.) **Reviewed Date:** March 28, 2018 **What do you like best about python-recsys?** the python-recsys Library (https://github.com/ocelma/python-recsys) offer us the opportunity to evaluate libraries in the field of machine learning for python, to test the technological bases for building recommendation systems. The solution makes use of the python libraries: python-scipy, python-numpy, csc-pysparse, networkx, divisi2. The solution offers recommendations and predictions to the users of a system, through the transformation of input data, based on reactions and transactions of the users and their relationship with the components of the products with which they interact. It makes use of the SVD (singular-value decomposition) functionality to apply a factorization process of the user's valuation data entry matrix. This solution can be used for the construction of systems that need to predict product recommendations, to its users, when there is a high number of products and users, efficiently taking advantage of the transactions and interactions of users and products. It is a good tool to learn about machine learning systems, making use of statistical algorithms and innovative development techniques, very well constructed, with some of the best programming languages that exist: python. Very good library. highly recommended its use and implementation **What do you dislike about python-recsys?** the libraries are not available for python 3.* **Recommendations to others considering python-recsys:** is a very good library for the construction of complex system of recommendations through factoring processes of input data valuation of a collaborative system **What problems is python-recsys solving and how is that benefiting you?** libraries could help me build a system to make recommendations to users about recipes according to the most popular products among users ### 14. Great for data visualization **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Government Administration | Enterprise (> 1000 emp.) **Reviewed Date:** October 29, 2018 **What do you like best about python-recsys?** Like other object based languages Python offers an initiative User experience **What do you dislike about python-recsys?** Lists can be confusing to create for those used to SAS **What problems is python-recsys solving and how is that benefiting you?** I have analyzed data ## python-recsys Discussions - [What is python-recsys used for?](https://www.g2.com/discussions/what-is-python-recsys-used-for) - [View python-recsys pricing details and edition comparison](https://www.g2.com/products/python-recsys/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-27+07%3A53%3A47+-0500&secure%5Bsession_id%5D=11e67cb8-c5ba-46d8-b1ca-0b5a00583cdc&secure%5Btoken%5D=00995bb0fe0f736521574afdc4f0e5094b9820186b50829e13d8e5f12a1e530c&format=llm_user) ## python-recsys Features **Integration - Machine Learning** - Integration **Learning - Machine Learning** - Training Data - Actionable Insights - Algorithm ## Top python-recsys Alternatives - [Alteryx](https://www.g2.com/products/alteryx/reviews) - 4.6/5.0 (773 reviews) - [Phrase](https://www.g2.com/products/phrase-phrase/reviews) - 4.5/5.0 (1,264 reviews) - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (650 reviews)