Spam Detection in Deep Learning

What is the so-called Spam?

E- messages are a crucial means of communication between many people worldwide. But several people and corporations misuse this facility to distribute unsolicited bulk messages that are commonly called Spam SMS. Spam SMS may include advertisements of medicine, software, adult content, insurance, or other fraudulent advertisements. Various Spam filters are wont to provide a protective mechanism that will design a system to acknowledge spam.

Spam Detection

After submitting your personal details like mobile number or email address on any platform, they started the advertisement of their unusual products by constantly pinging you. They try to advertise by sending constant emails and with the help of your contact details they keep sending you messages as well they are doing WhatsApp more nowadays. Hence, the output is nothing but a lot of spam alerts and notifications popping up in your inbox. This is often where the task of spam detection comes in.

Spam detection means detecting spam messages or emails by understanding text content in order that you’ll only receive notifications regarding your messages or emails that are crucial to you. If spam messages are found, they’re automatically transferred to a spam folder and you’re never notified of such alerts. This helps to enhance the user experience, as many spam alerts can bother many users. Read more…

The Future of Deep Learning Is Photonic

Think of the many tasks to which computers are being applied that in the not-so-distant past required human intuition. Computers routinely identify objects in images, transcribe speech, translate between languages, diagnose medical conditions, play complex games, and drive cars.

The technique that has empowered these stunning developments is called deep learning, a term that refers to mathematical models known as artificial neural networks. Deep learning is a subfield of machine learning, a branch of computer science based on fitting complex models to data.

While machine learning has been around a long time, deep learning has taken on a life of its own lately. The reason for that has mostly to do with the increasing amounts of computing power that have become widely available—along with the burgeoning quantities of data that can be easily harvested and used to train neural networks.

The amount of computing power at people’s fingertips started growing in leaps and bounds at the turn of the millennium, when graphical processing units (GPUs) began to be harnessed for nongraphical calculations, a trend that has become increasingly pervasive over the past decade. But the computing demands of deep learning have been rising even faster. This dynamic has spurred engineers to develop electronic hardware accelerators specifically targeted to deep learning, Google’s Tensor Processing Unit (TPU) being a prime example.

Here, I will describe a very different approach to this problem—using optical processors to carry out neural-network calculations with photons instead of electrons. To understand how optics can serve here, you need to know a little bit about how computers currently carry out neural-network calculations. So bear with me as I outline what goes on under the hood.

Almost invariably, artificial neurons are constructed using special software running on digital electronic computers of some sort. That software provides a given neuron with multiple inputs and one output. The state of each neuron depends on the weighted sum of its inputs, to which a nonlinear function, called an activation function, is applied. The result, the output of this neuron, then becomes an input for various other neurons. Read more

DataStage Developer

Title: -Datastage Developer
Location:-    Charlotte, NC
Duration: Full Time Permanent Position
Job Description:


*          At least 3 years of experience in software development life cycle
*          At least 3 years of experience in Project life cycle activities on development and maintenance projects
*          At least 1 year of experience in Relational Modeling, Dimensional Modeling and Modeling of Unstructured Data
*          Good experience in end-to-end implementation of DW BI projects, especially in data warehouse and mart developments
*          Good understanding of Data integration, Data Quality and data architecture
*          Experience to Big data technologies is preferred.
*          Good expertise in impact analysis due to changes or issues
*          Experience in preparing test scripts and test cases to validate data and maintaining data quality
*          Strong understanding and hands-on programming/scripting experience skills – UNIX shell, Perl, and JavaScript
*          Experience with design and implementation of ETL/ELT framework for complex warehouses/marts. Knowledge of large data sets and experience with performance tuning and troubleshooting

Data Warehouse Developer

Data Warehouse Developer

Richfield, MN, 55423

8 + Months – Long Term

5-10 years experience – OLAP/DSS/Data mining, designing and developing enterprise-wide repositories utilizing SQL-based data base products including DB2, SQL Server, Oracle, Sybase and other decision support systems/expert systems. Defines requirements and tools to interface all legacy data.

Define usage of queries/reporting tools to support, analyze large volumes of information within corporate data warehouse.

Experience with ETL tools(preferably Informatica, power center, Developer, power exchange), Relational databases(Oracle, SQL Server etc).

Experience with HDFS, hive and big data tools(spark, scala, sqoop etc preferable). Any scripting and cloud experience is a plus.

Quick learner and ability to handle multiple project independently/with minimal guidance

AS400 System Admin

Job Title:        AS400 System Admin
Location:        St. Petersburg, FL
Duration:       12+ Months

Job Description:
Experience working in AS400 administration in TCP/IP networked environment required.
Must have in-depth knowledge of AS400 hardware and software.
Proficient in AS400 LPARs, HMC, OS/400 (IBM i v7.x), IBM BRMS, CL and iSeries Navigator. Experience of Aldon LMI and Halcyon Messenger or similar software is a plus.
Hands-on knowledge of Microsoft Windows environments, including Windows 10, Windows CE/Mobile and Client Access for Windows.