Top 12 Artificial Intelligence Tools and Frameworks for 2021

Are you ready to Welcome 2021 with Artificial Intelligence trending everywhere? Here’s presenting a compilation of top AI tools and frameworks for 2021.

According to a study done by Grand View Research, “Artificial Intelligence Market Size Worth $390.9 Billion By 2025.”

Artificial Intelligence has made its way in every industry and has simplified our lives to a greater extent.

Besides these applications, it has also given rise to a number of tools frameworks.

The task of developers has been made easier with the help of these tools and frameworks in the same way as AI has made our personal and professional lives.

So let’s see what will rule in 2021.

Top 12 Artificial Intelligence Tools and Frameworks that will dominate in 2021

1. TensorFlow

Developed by Google Brain, TensorFlow is an open-source library perfect for handling huge volumes of complicated numerical computations.

Many giant companies like Google, SAP, Intel and Nvidia use TensorFlow.

It is multi-layered hubs that allow developers to set up, train and send counterfeit neural systems with massive datasets.

2. Keras

Keras is one of the most popular Python-based library frameworks that is considered as a best tool for handling problems like network configuration, image recognition and choosing the best architecture for specific situations.

It can run on the top of other frameworks such as TensorFlow or Theano.

It has a distinct feature that enables it to convert into other frameworks.

3. Scikit- Learn

SciKit-Learn is built upon Python’s two widely used libraries- NumPy and SciPy. It is open-source and developed in the year 2007. 

For standard AI and data mining functions, it includes various administered and unsupervised learning calculations such as bunching, choice trees, relapse, order, etc.

For dealing with data analysis, data mining and AI computation, Scikit-learn is considered as an excellent option.

4. Mxnet

Mxnet is built with scalability and has various other cool features such as writing custom layers in high-level languages with ease.

It is an open-source, community-developed framework and not directly governed by a single corporation.

It has TVM support which further improves deployment support. 

5. Theano

Theano is a library of Python which is best suitable for working with complex mathematical expressions.

It enables us to define and evaluate math expressions consisting of multi-dimensional arrays.

Theano is just folded over keras that runs parallely with the Theano library. 

6. Caffe

It is created by Berkeley Vision and Learning Center(BVLC) and community donors.

It is a versatile ML framework and thus considered as the most preferred choice for computer-vision tasks.

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

7. PyTorch

PyTorch is designed to speed up the process from research prototyping to production deployment.

It is an open-source ML framework created by Facebook.

PyTorch has various features such as distributed training, TorchScript, python-First.

8. Auto ML

Auto ML is one of the most powerful and latest additions to the collection of tools for the use by Machine learning engineers.

It is specially for the purpose of optimizing machine learning models.

It saves a lot of time and is extremely beneficial for the one having less experience in the field of machine learning. 

9. OpenNN

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

It is an open-source library that comes with extensive documentation and unit testing features.

OpenNN provides high processing speed and optimal memory management.

10. Microsoft Cognitive Toolkit (CNTK)

Microsoft Toolkit is a toolkit for Deep Learning that allows developers to combine different model types such as convolutional nets (CNN), Deep forward DNNs, and recurrent networks( RNNs/LSTMs).

It is an open-source toolkit which can be either used as a standalone ML tool through BrainScript or as a library in Python/C++/C# programs.

11. Google ML Kit

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

It is actually Google’s ML SDK that is particularly designed for mobile app development and is used to build highly customized features.

The kit has NLP APIs, video and image analysis APIs, and the cutting-edge AutoML vision edge feature.

12. H2O: Open Source AI Platform

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

It is designed by H2O.ai and mostly used for predictive data analytics by Ai developers and researchers.

H2O enables data-driven decision making and is also used to analyze cloud datasets in Apache Hadoop file systems. 

Conclusion

These are the most important Artificial Intelligence tools and frameworks that will be in most demand in 2021.

Experts using these tools and frameworks in a better way will definitely bring a radical transformation in various industries.