Deep Learning

Deep Learning

Deep learning and its representation of the human brain based on applied math and statistics has drawn a new way to solve machine learning problems. Deep learning is a must-have for important data businesses online today. However, deep learning technology is already being used in other industries too.

Deep learning and its representation of the human brain based on applied math and statistics has drawn a new way to solve machine learning problems. Deep learning is a must-have for important data businesses online today. However, deep learning technology is already being used in other industries too. If you want to outsource a project to developers in order to create AI solutions for image recognition, smarter predictions, or industrial design improvement, then you’ve got to choose Nestack as your partner.

Deep Learning is most definitely referred to the Neural Networks which are based on the functionality of brain neurons. Their functionality is expressed in term of complex mathematical equations which demonstrate the working of neurons in the brain. Neural networks have been used to solve different problems ranging from natural language processing, computer vision, sentiment analysis, voice recognition, and autonomous vehicles.

DeepDetect

OS: Windows, Linux, macOS
Groups like Microsoft and Airbus use DeepDetect, an open-source deep learning server which offers sensible API for image classification, object detection, and numerical and textual data analysis. DeepDetect is based on Caffe, XGBBoost, and TensorFlow.

Theano

OS: Windows, Linux, macOS
Theano puts itself out there as “a Python library that allows you to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently”. Theano is useful for deep learning operations and includes GPU support, NumPy integration, dynamic C code generation, and good symbolic differentiation.

Microsoft Cognitive Toolkit

OS: Windows, Linux
The Microsoft Cognitive Toolkit, previously named CNTK, offers the opportunity to train deep-learning algorithms to think like real human brains. It’s used by Microsoft to power the AI features they offer in Cortana, Bing, and Skype. The Microsoft Cognitive Toolkit offers scalability, commercial-grade quality, and speed, and is compatible with Python and C++.

Caffe

OS: Windows, Linux, macOS
A UC Berkeley PhD student was the original creator or Caffe, which has since become a popular deep learning framework. It is well-known for its expressive architecture, extensible code, and speed.

CaffeOnSpark

OS: Windows, Linux, macOS
CaffeOnSpark was a Yahoo project which brings the well-known deep learning framework of Caffe to Spark and Hadoop clusters. It has since come to be used for image search, content classification, and a range of other cases.

ConvNetJS

OS: Linux
ConvNetJS is a JavaScript library which makes it easy for developers to train deep learning models from browsers. It offers a no-sweat approach to training, promising “no software requirements, no compilers, no installations, no GPUs”.

DSSTNE

OS: Windows, Linux, macOS
The Deep Scalable Sparse Tensor Network Engine, or DSSTNE, is the software library of choice for Amazon. The e-commerce giant uses DSSTNE to train and run its recommendation engine. Core features of DSSTNE include its large layers, multi-GPU scale, and good operation with sparse datasets.

H2O

OS: Windows, Linux, macOS
H2O has more than 100,000 users and describes itself as “the world’s leading open source deep learning platform”. There is an open-source version and a premium edition of the platform which offers paid support.

Deeplearning4j

OS: Windows, Linux, macOS Deeplearning4j describes itself as “the first commercial-grade, open-source, distributed deep-learning library written for Java and Scala”. It also offers commercial support through Skymind.

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