About

An Azure product Torch: A scientific computing framework for LuaJIT powered by Miri Infotech. Torch is a suite of business tools that uses data mining, machine learning and artificial intelligence to automate work, save money and help in business grow. On Torch you can manage warehouse and store inventory, provide real time shipping costs to customers, and optimize your sales process. By capturing and analyzing data, Torch learns about your customers, allowing you to provide better online service without investing additional resources.

We are launching a product which will configure and publish Torch , business tools which is embedded pre-configured tool with LAMP and ready-to-launch Machine Image on Azure cloud that contains Torch, Apache, MySQL, Linux, PHP (LAMP).

Torch is the all-in-one artificial intelligence powered business suite. It provided everything you need to build, manage, and grow your company in a single platform. Check out some of the features below.

Torch is a scientific computing framework with wide support for machine learning algorithms that puts GPUs first. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation

User interaction features include:

a powerful N-dimensional array
lots of routines for indexing, slicing, transposing, ...
amazing interface to C, via LuaJIT
linear algebra routines
neural network, and energy-based models
numeric optimization routines
Fast and efficient GPU support
Embeddable, with ports to iOS, Android and FPGA backends

Torch packages provides:

Tensor Library

Tensor defines the all powerful tensor object that provides multi-dimensional numerical arrays with type templating.
Mathematical operations that are defined for the tensor object types.
Storage defines a simple storage interface that controls the underlying storage for any tensor object.

File I/O Interface Library

File is an abstract interface for common file operations.
Disk File defines operations on files stored on disk.
Memory File defines operations on stored in RAM.
Pipe File defines operations for using piped commands.
High-Level File operations defines higher-level serialization functions.

Useful Utilities

Timer provides functionality for measuring time.
Tester is a generic tester framework.
CmdLine is a command line argument parsing utility.
Random defines a random number generator package with various distributions.
Finally useful utility functions are provided for easy handling of torch tensor types and class inheritance.

Usage/ Deployment Instructions

1: Access Torch in Azure Marketplace and click on get it now button.

Click on GET IT NOW and then click on create,

2: Now to create a virtual machine, enter or select appropriate values for zone, machine type, resource group and so on as per your choice.

Click on Review + create;

After your deployment is complete.

To access the application:

Step 1: Do ssh into your VM then use following commands,

$sudo su

$th

Enjoy your application.

All your queries are important to us. Please feel free to connect.

24X7 support provided for all the customers.

We are happy to help you.

Submit your Query: http://www.miritech.com/ContactUs.aspx

Contact Numbers:

(510) 298-5936
(510) 870-8668

Contact E-mail:

support@miritech.com

Submit Your Request

Name:*

Email Address:*

Phone Number:

Company/Organisation:

Country:

Message:

Submit

You can subscribe to this product from Azure Marketplace and launch an instance from the product's image using the Azure compute service.

Type virtual machines in the search.
Under Services, select Virtual machines.
In the Virtual machines page, select Add. The Create a virtual machine page opens.
In the Basics tab, under Project details, make sure the correct subscription is selected and then choose to Create new resource group. Type myResourceGroup for the name.*.
Under Instance details, type myVM for the Virtual machine name, choose East US for your Region, and choose Ubuntu 18.04 LTS for your Image. Leave the other defaults.
Under Administrator account, select SSH public key, type your user name, then paste in your public key. Remove any leading or trailing white space in your public key.
Under Inbound port rules > Public inbound ports, choose Allow selected ports and then select SSH (22) and HTTP (80) from the drop-down.
Leave the remaining defaults and then select the Review + create button at the bottom of the page.
On the Create a virtual machine page, you can see the details about the VM you are about to create. When you are ready, select Create.

It will take a few minutes for your VM to be deployed. When the deployment is finished, move on to the next section.

Connect to virtual machine

Create an SSH connection with the VM.

Select the Connect button on the overview page for your VM.
In the Connect to virtual machine page, keep the default options to connect by IP address over port 22. In Login using VM local account a connection command is shown. Select the button to copy the command. The following example shows what the SSH connection command looks like:

bashCopy

ssh azureuser@10.111.12.123

Using the same bash shell you used to create your SSH key pair (you can reopen the Cloud Shell by selecting >_ again or going to https://shell.azure.com/bash), paste the SSH connection command into the shell to create an SSH session.

1What is big data security analytics?

Add the words “information security” (or “cybersecurity” if you like) before the term “data sets” in the definition above. Security and IT operations tools spit out an avalanche of data like logs, events, packets, flow data, asset data, configuration data, and assortment of other things on a daily basis. Security professionals need to be able to access and analyze this data in real-time in order to mitigate risk, detect incidents, and respond to breaches. These tasks have come to the point where they are “difficult to process using on-hand data management tools or traditional (security) data processing applications.”
2Is there an easy way to migrate data from Hadoop into a relational database?

The Hadoop JDBC driver can be used to pull data out of Hadoop and then use the DataDirect JDBC Driver to bulk load the data into Oracle, DB2, SQL Server, Sybase, and other relational databases.
3Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

Front-end use of AI technologies to enable Intelligent Assistants for customer care is certainly key, but there are many other applications. One that I think is particularly interesting is the application of AI to directly support — rather than replace — contact center agents. Technologies such as natural language understanding and speech recognition can be used live during a customer service interaction with a human agent to look up relevant information and make suggestions about how to respond. AI technologies also have an important role in analytics. They can be used to provide an overview of activities within a call center, in addition to providing valuable business insights from customer activity.
4What are the popular machine learning algorithms in use today?
There are many machine learning algorithms in use today, but the most popular ones are:
- Decision Trees
- Naive Bayes Classification
- Ordinary Least Squares Regression
- Logistic Regression
- Support vector machines
- Ensemble Methods
- Clustering Algorithms
- Principal Component Analysis
- Singular Value Decomposition
- Independent Component Analysis

Torch

About

Submit Your Request

1What is big data security analytics?

2Is there an easy way to migrate data from Hadoop into a relational database?

3Are Intelligent Assistants the only application of AI for customer care, or are there other ways that AI technologies can impact the contact center?

4What are the popular machine learning algorithms in use today?

Highlights

Application Installed