The main Deep Learning tools.

The main Deep Learning tools
DEEP LEARNING The main Deep Learning tools.
  • 24-06-2022
  • DEEP LEARNING

Deep learning applications are used in different types of industries. Considering the impact of deep learning in the world, in this article here you could study seven deep learning tools.

Here are some of the best deep learning tools. Though this list is by no means exhaustive! There are more deep learning tools in the market but these are the ones that are used the most.

  1. H2O.ai

H2O is a deep learning tool that was built from scratch in Java and follows a seamless integration with other open source products like Apache Hadoop and Spark. It has an easy to use Web UI and is massively scalable in big data analysis.

  1. TensorFlow

TensorFlow is a deep learning tool that was written in highly-optimized C++ and CUDA (Nvidia’s language for programming GPUs) and provides an interface to languages like Python, Java, Go. It is an open-source library that was developed by the tech giant, Google, for the smooth running of deep learning applications.

TensorFlow makes it fairly easy for beginners and even experts to create machine learning models for mobile, web, desktop, and cloud.

  1. Keras

Keras is a high-level neural network API that is capable of running on top of TensorFlow or Theano. It is written in Python and was developed mainly on enabling faster experimentation. Keras deep learning library allows the user for easier and faster prototyping with the use of modularity, minimalism and easy extensibility.

  1. Caffe

Caffe is a deep learning tool whose framework is built with expression, speed and modularity in consideration. Developed by the Berkeley AI Research (BAIR)/The Berkeley Vision and Learning Center (BVLC) and community contributors, it is also an open source deep learning tool.

  1. DeepLearningKit

DeepLearningKit is an open source deep learning tool for Apple’s iOS, OS X, tvOS, etc. The main idea behind its creation was to support pre-trained models on all the Apple devices that have a GPU. This deep learning tool is developed in Swift and can be used on device GPU to perform low-latency deep learning calculations. DeepLearningKit supports Convolutional Neural Networks too. Its vision is to support other deep learning tools like Torch and TensorFlow.

  1. Torch

Torch is an efficient open source program that uses a LuaJIT scripting language and C/CUDA implementation. If you are using this deep learning tool, you will be able to take advantage of its powerful features like: multiple routines for indexing, transposing, slicing, amazing interface to C via LuaJIT, neural network. It offers fast, efficient GPU support and is easily embeddable that makes it easier to work with iOS, Android, FPGA.

  1. Theano

Theano is a Python library that is used to evaluate mathematical operations including multi-dimensional arrays. It is mainly used in building deep learning projects and is way faster on a GPU than a CPU. With its use, it is possible to attain speed that rivals self-made C implementations for problems that involve large amounts of data.