Top Artificial Intelligence Tools And Frameworks That Will Dominate In 2021

CIOReviewIndia Team | Friday, 08 January 2021, 12:54 IST

In this first week of 2021, experts have gathered data and predicted that artificial intelligence and other related technologies which prevailed in the previous year, will get help from tools and frameworks such as TensorFlow or Keras.

As per stats suggest by Grand View Research, by 2025, Artificial Intelligence will be worth almost $390.9 billion.

Artificial Intelligence has entered every industry and has extended helping hands by simplifying their lives.

It has been responsible for the development of several tools and frameworks.

A developer’s task has become simplified due to these tools and frameworks equivalently how AI has made personal and professional lives easy.

These are the tools and frameworks which will help AI professionals –

TensorFlow –

TensorFlow is developed by the Google brain. It is an open-source library which is perfect for handling huge volumes of complicated numerical computations.

Topnotch companies like Google, SAP, Intel and Nvidia use TensorFlow.

TensorFlow is multi-layered hubs, which allows developers set up, train, and send counterfeit neural systems with massive datasets.

Keras –

Being one of the most popular Python-based library frameworks, Keras is considered a best tool for handling problems like network configuration, image recognition, and selecting the best architecture for particular problems.

Keras can run on the top of other frameworks like TensorFlow or Theano, and has a distinct feature, which enables it to convert into other frameworks.

Scikit-Learn –

Built on Python’s two majorly used libraries – NumPy and SciPy, Scikit-Learn is open source and developed in 2007.

SciKit-Learn is used for standard AI and data mining functions, including various administered and unsupervised learning calculations like bunching, choice trees, relapse, and order.

SciKit-Learn can also be used for data analysis, data mining and AI computation.

Mxnet –

Mxnet is developed with scalability and has various other modern features like writing custom layers in high-level languages with ease. It is also an open-source, community-developed framework, and not directly governed by a single corporation.

Mxnet has TVM support which further improves the deployment support.

Theano –

Theano is a library of Python which is extremely helpful for working with complex mathematic expressions.

Theano helps in defining and evaluating math expressions consisting of multi-dimensional arrays.

Caffe –

Caffe is developed by Berkeley Vision and Learning Center (BVLC) and community donors. It is a versatile ML framework and is preferred by many for computer-vision tasks.

Caffe has the most-sophisticated and expressive architecture that encourages innovation and speed.

PyTorch –

Designed for speeding up the process from research prototyping for production deployment, PyTorch is an open-source ML framework created by Facebook.

PyTorch has features of various kinds like distributed training, TorchScript, Python-First.

Auto ML –

A powerful and latest addition to the collection of tools, Auto ML is used by many machine learning engineers.

It is specifically used for the purpose of optimization of machine learning models.

Auto ML saves a lot of time and is extremely beneficial for the one with less experience in the field of machine learning.

OpenNN –

Programmed in C++, OpenNN (Open Neural Networks Library) is designed for Deep Learning and advanced ML research.

OpenNN is an open-source library which has extensive documentation and unit testing features.

It provides high processing speed and optimal memory management.

Microsoft Cognitive Toolkit (CNTK) –

A toolkit for Deep Learning, Microsoft Cognitive Toolkit (CNTK) allows developers to adjoin different model types like convolutional nets (CNN), Deep forward DNNs, and recurrent networks (RNNs/LSTMs).

Microsoft Cognitive Toolkit (CNTK) is an open-source toolkit which can either be used as a standalone ML tool through BrainScript or as a library in Python/C++/C# programmes.

Google ML Kit –

Google ML Kit allows developers to develop mobile apps for both android and iOS platforms.

Google ML Kit is primarily Google’s ML SDK which is particularly designed for mobile application development and is used to build highly customized features.

Google ML Kit has NLP APIs, video, image analysis APIs, and the cutting-edge AutoML vision edge feature.

H2O: Open Source AI Platform

H2O is an open-source ML software tool programmed in Python, R, and Java programming languages.

H2O is designed by H2).ai and is favorably used for predictive data analytics by AI developers and researchers.

H2O enables data-driven decision concepts and is also used for analyzing cloud datasets in Apache Hadoop file systems.

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