Best 10 Artificial Intelligence Tools for Future World

6. Apache MX Net:

Apache MX Net is an open-source deep learning framework developed by Apache Software Foundation. It is written in multiple languages, including Python, C++, and R, and supports multiple platforms. It is optimized for distributed training and is designed to scale to multiple machines and GPUs.

It supports a wide range of network architectures, including convolutional neural networks, long short-term memory networks, and recurrent neural networks.

This Artificial Intelligence tool is adopted by big industries like Amazon as its deep learning framework on AWS.

7. Keras:

Keras is one of the open-source neural network libraries written in Python programme. This is designed to be used with either. It is designed to enable fast experimentation with deep neural networks is capable of running on top of multiple back-end engines such as Tensor Flow.

Microsoft Cognitive Toolkit(CNTK) and Theano.It supports multiple types of networks, including convolutional, recurrent, and even a combination of multiple networks.

This AI tool is  is extremely user-friendly tool is built on top of TensorFlow and is comparatively easier to use as well. This tool is  used for first prototyping that facilities the completion of state-of-the-art experiments from start to end with little or no delay. This tool popularly run seamlessly on CPU and GPU.

8.OpenNMS:

Open NN is an open-source machine-learning library for C++ and Python. It is designed to help developers create and train deep learning models quickly and efficiently.

It provides a wide range of features including convolutional neural networks, recurrent neural networks, and long-term memory networks. It supports distributed training and can be used on GPUs and CPUs.It is designed to be easy to use and provides developers with a wide range of tools for creating and training deep learning models. 

This library is written++ language. This AI tool offers a platform for developers wanting to upgrade to advanced analytics.

9. AutoML:

Auto ML is a type of artificial intelligence (AI) that automates the process of creating and training machine models. It is used to automate the process of feature engineering, model selection, hyperparameter, tuning and model evaluation.

AutoMLis are especially useful for applications that require complex models, such as computer vision and natural language processing. It is used by both researchers and developers to quickly build and deploy powerful machine-learning models.

This is one of the top Artificial Intelligence tools in the world, which is currently at the disposal of machine learning engineers all over the world. This Artificial Intelligence I tool automates the processes involved in articulating a real-world problem using machine learning techniques in the world.

10.H2O:

H2O is an open-source machine-learning platform developed by Oxdata. It is used and deploy predictive models. It provides a wide range of features including automatic machine learning, deep learning, and statistical modeling.

It supports a variety of languages including Python, R, Scala, and Java. It also supports distributed training, enabling developers to train models on multiple machines and GPUs.

This Artificial Intelligence tool is an open-source deep learning platform and business oriented. This tool helps draw insightful decisions on business from the data at disposal.

H2O is written in Java and includes an interface for Python, R, Java, Scala, Coffee Script, and JSON.