Deep Learning -Tools.txt - A deep net platform is service...

A deep net platform is service that allows you to incorporate deep net in our
applications without building one from scratch. This platform provides a set of
tools and interface to build your own custom deep net.
Deep net platforms are of two types.
Software platform: This platform is available as downloadable packages that need
to be deployed on your hardware.
Full platform: It is available as online interactive UI to build and deploy
models without any coding experience.
The following are the tools offered by deep net platforms.
Deep Net capability
Data Munging
UI/Model Management
Infrastructure
Using Deep Net Capability tool, the user can choose among various available deep
nets depending on the use case. For example, you can select convolutional net
for image recognition or RNTN for text analysis and so on.
Data Munging tool enables us to import data (structure or unstructured) from
various sources and manipulate it to feed into a selected deep net.
In order to train a significant amount of data and increase performance, some
platforms provide infrastructure facilities like built-in integration tools such
as Amazon S3, SQL, and NoSQL.
H2O.ai is an opensource machine learning platform. Along with many machine
learning algorithms, this platform currently provides one deep net capability
that is Multilayer Perceptron.
It offers intuitive UI and powerful data munging capabilities.
It is available as a downloadable package that has to be installed and managed
in our own hardware infrastructure.
H2O.ai supports machine learning models as GLM, Distributed random forest, K-
means clustering, gradient boosting machine, a Cox proportional hazard and Naive
Bayes classifier.
Supports Multilayer perceptron for deep learning model which uses L-BFGS
algorithm for backpropagation.
H2O.ai offers built-in integration tools for platforms like HDFS, Amazon S3,
SQL, and NoSQL.
Platform's intuitive UI can be accessed by programming environments like R,
Python, and JSON.
You can model and analyze data with Tableau, Microsoft excel and RStudio.
Since you need to download the package and deploy in your hardware, H2O.ai comes
with in-memory map reduce, columnar compression to help speed the training of
models.