Most Popular Machine Learning Software Tools, 2021

Artificial intelligence (AI) is the wider term with machine learning as one of its applications. Machine learning enables the systems to study and come up with an improved experience. It emphasizes the development of computer-based programs that can have an access to the data and use it to derive conclusions for business growth and other complexities of business. 

Machine learning aids us through sturdy processing. Quick and accurate decision making is facilitated by it and ensures better decisions despite being reasonably cheap. There is no restriction over the quantum of data as it can process even complex data in great quantities. Supervised, unsupervised and reinforcement are the three types of machine learning.

 Effective and popular Machine Learning software that are in rage these days -

Scikits-learn

It is a free machine learning software having a library for the Python programming language. It aids in data mining and analysis along with features of the clustering algorithm, regression, classification, dimensional reduction, preprocessing and selection of the model. The feature of support vector machines is also present in this software. Records rendered by it are simple to understand. However, parameters for any particular algorithm can be altered too. 

 Shogun

Shogun software is a storehouse of numerous data structures and algorithms for machine learning. It is mainly used in the realm of research and education. The Hidden Markov model is executed with the aid of it. It also caters assistance to vector machines for classification and regression. Languages like Octave, R, Java, Scala, Python and Lua are supported by it. ML also can process data on large scale along with being highly simple to bring into play. It caters great support to customers.

 PyTorch

Pytorch is free software with open source. This machine learning library is based on the Torch library. It is put in use for language processing and computer vision applications. It was developed by the research lab of Facebook. With the aid of the Autograd Module, Pytorch helps in formulating neuron networks. Cloud platforms also support Pytorch. It involves a range of tools and libraries. The hybrid front end makes it handy. Pytorch is also quite versatile in fabricating computational graphs.  

Apache Mahout

This software is a boon for mathematicians, data scientists and statisticians in implementing their algorithms. It extends the algorithm for clustering, linear algebra, pre-processors, etc. It comprises Java libraries for common operations of mathematics. It is again simple and uncomplicated software suitable for huge data. Some cons are also realized in it like some of the algorithms seem missing. Like the above-stated software, it is also free.

 KNIME

It focuses on the data pipelining concept and merges distinct components of data mining and machine learning. It is said to be the key to data analytics, reporting and integration programs. The software is potent in integrating the code of C, Python, R, Javascript, Java, etc. It is completely free and is simple to use and install. It can operate as a SAS option. It is however associated with cons too. Knime lays constrictions on restricted visualization and exporting of information. They do not support the development of complex models. It is free.                                                                                                                                                                                                                                                                                                                                                         Weka

Weka, the ML algorithm is immensely useful for data mining. It is considered great for students. One can enrol themselves in online training to learn as it extends training too in this algorithm. It is a free of cost algorithm. It is multi-tasking software that aids in data preparation, classification, regression, clustering, visualization and rules mining of association/company. The cost of this tool is nil as it is free. But it doesn't entail much online support and documentation.

 Colab

This cloud service aids python completely. You can build machine learning applications like Pytorch, OpenCV, Keras, and TensorFlow. It is being used in providing education regarding machine learning along with making related research. It is a completely free cloud service that can be used from the Google drive of an individual.

The bottom line:

Selection from above or other software should be done based on a required algorithm, your proficiency and the cost of the tool. The library of machine learning shouldn't be complex to understand rather should be simple to have in use. Most of the libraries are free of cost not requiring you to spend money on the tool.