One of the fastest-growing areas in computer science is Artificial intelligence. It has many practical applications in our everyday lives such as search engines, speech recognition software, machine translation, and autonomous vehicles.

Some of the things we see done today by artificial intelligence are accomplished through the use of specific tools and frameworks.

 What is an Artificial intelligence framework?

As explained by Intel, AI frameworks provide data scientists, AI developers, and researchers the building blocks to architect, train, validate, and deploy models through a high-level programming interface. 

Top 6 Artificial Intelligence Frameworks:

There are many types of artificial intelligence frameworks out there, but here are the top six.

-TensorFlow

– Keras

-Py Torch

-Scikit-Learn

-Caffe

-Theano

Tensor Flow

TensorFlow is an open-source library for machine learning created by Google. Companies such as Google, Facebook, and Microsoft use it.

On your phone, it is also used by Amazon Alexa and Apple Siri.

– Keras

Keras is an open-source software library that provides a Python interface for artificial neural networks. It acts as an interface for the TensorFlow library. Keras runs smoothly on both CPU and GPU.

It is used by nearly every major technology company, including Facebook, Google, Microsoft, and Amazon.

-Py Torch

Py Torch is a python package developed by Facebook. It is an AI researcher’s open-source ML and deep learning framework.

Py torch provides a function for deploying mobile and embedded frameworks.

-Scikit-Learn

Scikit-Learn is a tool used for data mining, data analysis, and model building. This tool is designed to operate with python libraries like NumPy, SciPy, and Matplotlib.

According to jigsaw academy Scikit learn underpins the unsupervised and administered calculations. The precedent can incorporate calculated and direct relapses, bunching, choice trees, etc.

Theano

The Theano is folded over the Keras. Keras is a Python library that allows for profound discovery and runs on TensorFlow or Theano. Theano was created to create models of profound learning that are simple and quick to implement in some innovative work. It runs on Python and can be executed on GPUs and CPUs. Theano can exploit the GPU of the PC. This allows it to make escalated information count many times more than when it is restricted to running solely on the CPU. Theano’s speed makes it extremely profitable to perform any complex computations.

-Caffe

Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by Berkeley AI Research (BAIR) and by community contributors. Yangqing Jia created the project during his Ph.D. at UC Berkeley. Caffe is released under the BSD 2-Clause license.

Conclusion

Artificial Intelligence tools are becoming easier to find and most importantly, they are getting more affordable than before. We hope that this list will help you make the best decision when you decide on what tool might be best for your next project.