scikit-learn
scikit-learn is a machine learning software that is available to everyone as it is offered completely free of cost. The software and its library machine is based on the well known Python programming language and comes along with numerous features and tools, making it a highly accessible platform for predictive data analysis.
Top scikit-learn Alternatives
- MATLAB
- Protégé
- Sparkling Water
- DataRobot
- TensorFlow
- Gensim
- Salesforce Einstein
- OpenAI Gym
- Theano
- Apache Storm
- IBM Watson Studio
- Azure Machine Learning Studio
- Domino Data Lab
- Big Squid
- Plotly
Top scikit-learn Alternatives and Overview
MATLAB
MATLAB is a data science and machine learning-based development toolkit that processes iterative formulas into computer-based processes.
DataRobot
DataRobot is a reliable enterprise AI platform that allows you to automate all the processes for building, deploying, and maintaining AI at large scales.
TensorFlow
TensorFlow is an open-source library with functions that enable easy implementation of end-to-end machine learning models and datasets.
Gensim
Gensim was developed in 2008, when it served as a form of digital library where it gave results of articles that sounded similar to the searched article.
Salesforce Einstein
Using artificial intelligence and machine learning on processes, it increases customer satisfaction by switching guesswork...
OpenAI Gym
The software has been created in such a manner that it supports a wide variety...
Theano
The software program has been developed in such a way that it allows its users...
Apache Storm
This open-source tool is compatible with several operating systems and is designed to deliver the...
Azure Machine Learning Studio
This GUI-based integrated platform assists developers and data scientists throughout the development lifecycle and helps...
Domino Data Lab
It allows the data scientists to process a vast amount of information with its platform...
Big Squid
It offers to consult for executives and business stakeholders to make optimized decisions and reap...
scikit-learn Review and Overview
The scikit-learn software was first published by David Cournapeau, way back in June 2007. For more than 12 years, the software has been helping developers to use the integrated features of the Python numerical (NumPy) and scientific libraries (SciPy) to provide better solutions.
An overview
The skicit-learn program was developed by its founder as part of a Google Summer Code Project. The software obtains its name from the fact that is a SciPy toolkit, which together makes it scikit. The software acts as a specifically designed third party application to the SciPy platform. However, as the project started getting recognition, more developers came together to build a much more advanced version of the original software by adding newer features and making the software even more powerful. The scikit-learn software has established its position as one of the most in-demand machines learning languages on GitHub.
Implementation
The developers of the scikit platform have mostly written the program in the Python programming language. The software provides easy integration with the numerical operations of Python and it uses them extensively to allow high-performance mathematical operations within the software. To further support high-performance output by the platform, some of the core algorithms have been written using the more advanced Cython programming language.
Conclusion
The scikit-learn platform is offered to users as open-source software, under the regulations of the BSD license. scikit-learn is used by some of the world’s most famous brands and corporations such as Spotify, JP Morgan and many more. The program has been designed in a way that it can be used by anyone, regardless of the professional background of the person. Although the software is offered completely free of cost, the donations and grants provided by institutions and corporate giants help the software to remain sustainable.
Company Information
Company Name: Microsoft
Founded in: 1975