The availability of different frameworks, libraries, and APIs allows for building machine learning apps faster. You don’t have to worry about building algorithms from scratch. Today, you can choose from a variety of machine learning solutions to build powerful software to facilitate business needs.
Let’s review some of the most popular machine learning frameworks.
TensorFlow is a popular framework from Google that is particularly suitable for building deep learning models. Such models use artificial neural networks to enable progressive learning and system improvements. The framework is based on a computational graph consisting of a network of nodes. Each now is an operation that performs some complex or simple function.
PyTorch is a direct competitor of TensorFlow as it provides huge capabilities for building deep learning models. It’s also a part of a bigger Torch deep learning framework developers use to build deep neural networks and perform complex computations.
If you want to know how to build a machine learning app for educational and research purposes, Shogun is a great solution. The framework can process large data sets and supports vector machines for regression and classification.
Apache Mahout targets mathematicians, data scientists, and statisticians who need help with algorithm execution. This framework has built-in algorithms for distributed linear algebra and concentrates on such tasks as collaborative data grouping, classification, and filtering.
Konstanz Information Miner (KNIME) is a great software used for data visualization, modeling, and analysis without complex coding. The framework uses a modular data pipeline concept combining different components for machine learning, and data mining is a single solution.
Weka comprises several machine learning algorithms used mainly for data mining. You can perform different functions with it, such as regression, classification, clustering, data preparation, and visualization. If you are just starting up in machine learning, it’s a great tool to explore.
RapidMiner is a comprehensive environment where you can perform different tasks, such as data preparation, machine learning, deep learning, text mining, and predictive analytics. This solution is widely used for education, research, and development purposes.
Below you can see a table comparing the most popular machine learning frameworks mentioned above.