Popular Artificial Intelligence Frameworks Developers Use
Artificial Intelligence tools are nothing but frameworks that help developers to build AI projects smoothly. They provide easy-to-use and efficient tools for data visualization, analytics, and machine learning.
Scikit-learn
It is one of the most powerful Open Source AI Development Tools Frameworks that uses a consistent interface in Python to provide learning algorithms either supervised or unsupervised. It encourages commercial and academic use. It includes functionality like clustering, Cross-Validation, Dimensionality reduction, feature selection, feature extraction, etc.
H2O
H2O Open source Al Platform or hybrid cloud is a commencement to conclusion stage that democratizes artificial intelligence, that lets employees, clients, and residents with modern Al innovation and Al applications that are available to use in a go.
Theano
Theano is a python library that helps in defining, optimizing, and evaluating mathematical expressions. It also supports expressions with multi-dimensional arrays and can reduce the compilation/ analysis overhead. It includes transparent usage of GPU, Symbolic differentiation, Dynamic generation of C code, Integration with NumPy, etc.
TensorFlow
TensorFlow is another important ML framework. Every issue faced by data analysts and developers is addressed in the updates. It includes features like Robust Production, Model building, support for powerful experiments, Distributed training, Accessible syntax, More network control, etc.
Apache Singa
Apache Singa is another open-source library that offers flexible architecture. With scalable distributed training it can easily be extended to be executed over a wide range of hardware and has major applications in the healthcare sector.
Caffe
Another artificial intelligence framework that is built with expression, speed, and modularity in consideration. It is easy to use as basically it is written in C++ with a Python interface. It includes Active development and supports expressive architecture without any hard coding, or model. It helped multiple startup prototypes, academic research projects, as well as large-scale industrial processes.
Keras
This open-source framework provides a Python interface for artificial neural networks. It acts better as an interface for the Theano & TensorFlow library. Our Al Solution providers make the best use of the framework to deliver solutions. It combines optimizer, neural layers, initialization schemes, cost functions, activation functions, and regularization schemes to build new models that help you stand ahead of your competition.
