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Foster your Machine Learning Efforts with these 5 Best Open Source Frameworks

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Foster your Machine Learning Efforts with these 5 Best Open Source Frameworks

Machine Learning is rapidly becoming the mainstream and changing the way we carry out tasks. While many factors have contributed to this current boom in machine learning, the most important reason is the wide availability of open source frameworks.

’Open source’ refers to a program that is created as a collaborative effort in which programmers improve the code and share the changes within the community. Open source sprouted in the technological community in response to proprietary software owned by corporations. The rationale for this movement is that programmers not concerned with proprietary ownership or financial gain will produce a more useful product for everyone to use. 

Framework: It refers to a cluster of programs, libraries and languages that have been manufactured for use in application development. The key difference between a library and a framework is ‘’inversion of control’’. When a method is summoned from a library, the user is in control. With a framework the control is inverted- the framework calls the user.

If you are plunging full-fledged into machine learning, then you clearly need relevant resources for guidance. Here are the top 5 frameworks to get you started.

  1. TensorFlow:

TensorFlow was developed by the Google Brain Team for handling perceptual and language comprehending tasks. It is capable of conducting research on machine learning and deep neural networks. It uses a Python-based interface. It’s used in a variety of Google products like handling speech recognition, Gmail, photos and search.

A nifty feature about this framework is that it can perform complex mathematical computations and observe data flow graphs. TensorFlow grants users the flexibility to write their own libraries as well. It is also portable. It is able to run in the cloud and on mobile computing platforms as well as with CPUs and GPUs.

  1. Amazon Machine Learning (AML):

AML comes with a plethora of tools and wizards to help create machine learning models without having to delve into the intricacies of machine learning. Thus it is a great choice for developers. AML users can generate predictions and utilize data services from the data warehouse platform, Amazon Redshift. AML provides visualization tools and wizards that guide developers. Once the machine learning models are ready  AML makes it easy to obtain predictions using simple APIs.

  1. Shogun:

 Abundant in state-of-the-art algorithms, Shogun makes for a very handy tool. It is written in C++ and provides data structures for machine learning problems. It can run on Windows, Linux and MacOS. Shogun also proves very helpful as it supports uniting with other machine learning libraries like SVMLight, LibSVM, libqp, SLEP, LibLinear, VowpalWabbit and Tapkee to name a few.

  1. NET:

Accord.NET is a machine learning framework which possesses multiple libraries to deal with everything from pattern recognition, image and signal processing to linear algebra, statistical data processing and much more. What makes Accord so valuable is its ability to offer multiple things which includes 40 different statistical distributions, more than 30 hypothesis tests, and more than 38 kernel functions.

  1. Apache Signa, ApacheSpark MLibApache, and Apache Mahout:

These three frameworks have plenty to offer. Apache Signa is widely used in natural language processing and image recognition. It is also adept in running a varied collection of hardware.

Mahout provides Java libraries for a wide range of mathematical operations. Spark MLlib was built with the aim of making machine learning easy. It unites numerous learning algorithms and utilities, including classification, clustering, dimensionality reduction and many more.

 With the advent of open source frameworks, companies can work with developers for improved ideas and superior products. Open source presents the opportunity to accelerate the process of software development and meet the demands of the marketplace.

Boost your machine learning endeavors by enrolling for the Apache Spark training course at DexLab Analytics where experienced professionals ensure that you become proficient in the field of machine learning.

 

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5 Examples that Show Artificial Intelligence is the Order of the Day of Daily Life

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Artificial Intelligence is no more an elusive notion from science fiction; in fact, it’s very much in use in everyday life. Whether you realize it or not, the influence of AI has grown manifold, and is likely to increase further in the coming years.

5 Examples that Show Artificial Intelligence is the Order of the Day of Daily Life

Here are a few examples of AI devices that lead you to a brighter future. Let’s have a look:

Virtual Personal Assistants

The world around you is full of smart digital personal assistants – Google Now, Siri and Cortana though available on numerous platforms, such as Android, Ios and Windows Mobile strives to seek meaningful information for you, once you ask for it using your voice.

In these apps, AI is the power giver. With the help of AI, they accumulate information and utilize that data to better understand your speech and provide you with favorable results that are tailor-made just for you.  

Smart cars

Do you fantasize about reading your favorite novel, while driving to office? Soon, it might be the reality! Google’s self-driving car project and Tesla “autopilot” characteristic are two latest innovations that have been stealing the limelight lately. In the beginning of this year, there was a report that, Google developed an algorithm that could potentially allow self-driving cars learn the basics of driving just like humans, i.e. through experience.

Fraud detection

Have you ever found mails asking if you have made any particular transaction using your credit card? Several banks send these kinds of emails to their customers to verify if they have purchased the same to avoid frauds being committed on your account. Artificial Intelligence is employed to check this sort of fraud.

Like humans, computers are also trained to identify fraudulent transactions based on the signs and indications a sample shows about a purchase.

Buying pattern prediction

Distinguished retailers, like Amazon do make a lot of money, as they anticipate the buyer’s needs beforehand. Their anticipatory shipping project sends you products even before you ask for them, saving you from the last-minute online shopping. If not online retailers, brick-and-mortar retailers also use the same concept to offer coupons; the kind of coupons distributed to the shoppers is decided by a predictive analytics algorithm.

Video games

Video games are one of the first consumers of AI, since the launch of the very first video games. However, over the years, the effectiveness and intricacies of AI has doubled, or even tripled, making video games more exciting, graphically and play wise. The characters have become more complex, and the nature of game-play now includes a number of objectives.

No matter, video games are framed on simple platforms, but as industry demand is burgeoning at an accelerating pace, a huge amount of money and effort are going into improving AI capabilities to make games more entertaining and downright exciting!

Fact: Artificial Intelligence is serving millions of people on earth today. Right from your smartphone to your bank account, car and even house, AI is everywhere. And it is indeed making a huge difference to all our lives.

To gain more knowledge on AI, enroll in Big Data Certification Gurgaon by DexLab Analytics. Their big data and data analytics training is of high quality and student-friendly. The prices of the course are also fairly convenient.

The blog has been sourced from – https://beebom.com/examples-of-artificial-intelligence

 

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5 Best Data Science Resources to Ace the Game of Data

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Wondering how a data scientist makes advances in his data career? Or how does he expand his skills in the future? Reading is the most common answer; nothing helps better than keeping a close eye on the industry news. Data science is evolving at a rapid speed; to be updated with the latest innovations and technology discoveries would be the best thing to stay ahead of the curve.

5 Best Data Science Resources to Ace the Game of Data

If you are a newbie in this field, make sure you are well-read about the current industry trends and articulate it well to the HR heads that you are someone who is always a step ahead to consume knowledge about data science and its related fields. This helps!

A wide number of data science blogs and articles are available over the internet, but with so many options, it’s easy to feel lost. For this and more, we have compiled a comprehensive list of 5 best data science blog recommendations that would help aspiring data scientists maneuver smoothly through this sphere.

Data Elixir

For a one stop destination for all things DATA, Data Elixir is the right choice. Crafted by ex-NASA data scientist Lon Riesberg, Data Elixir offers a list-wise view of the posts; easy categorization of content is anytime preferable and renders easy search options.

Data Science Weekly

The brain child of Hannah Brooks and Sebastian Gutierrez, Data Science Weekly is the ultimate hub for recent news, well-curated articles and promising jobs related to data science. You can either sign up for their newsletter or simply scroll through their archives dated back to 2013.

The Analytics Dispatch

The Analytics Dispatch is more like a newsletter content creating hub, wherein they send weekly emails about data science related stuff to its readers. Collected, analyzed and developed by a robust team at Mode Analytics, which also happens to be an Udacity partner, the newsletters focus on practical advices on data analysis and how data scientists should work.

Let’s Take Your Data Dreams to the Next Level

O’Reilly Media’s data science blog

To read some of the most amazing articles on AI and data science, make O’Reilly Media’s data science blog your best companion. The articles are curated, researched and written by influencers and data science pundits, who are technically sound and understands the advanced nuances of the field in-depth.

Cloudera

Being top notch big data software, Cloudera’s contribution to the world of data science is immense. Time to time, it publishes interesting articles, know-hows and guides on a plethora of open source big data software, like Hadoop, Flume, Apache, Kafka, Zookeeper and more.

Besides, DexLab Analytics, a pioneering analytics training institute headquartered in Gurgaon, India also publishes technical articles, amazing blogs, riveting case studies and interviews with analytics leaders on myriad data science topics, including Apache Spark, Retail Analytics and Risk Modeling. The content is crisp, easy to understand and offers crucial insights on a gamut of topics: it helps the aspiring readers to broaden their horizons.

The realms of data science are fascinating and intimidating as well; but with the right knowledge partner, carry suave data skill in your sleeves – Data Science Courses in Noida from DexLab Analytics are the best in town! Also, their Business Analytics Training Courses in Noida are worth checking for.

Some of the parts of the blog have been sourced from – http://dataconomy.com/2018/01/5-awesome-data-science-subscriptions-keep-informed/ and https://www.springboard.com/blog/data-science-blogs

 

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How Artificial Intelligence is Boosting the Design of Smarter Bionics

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How Artificial Intelligence is Boosting the Design of Smarter Bionics

Artificial Intelligence and Machine Learning are a set of technologies that empower machines and computers to learn and evolve upon their own learning through constant reiteration and consistent data bank upgrades. The entire chain of mechanism stands on recursive experiments and human intervention.

Bionics

Advances in technology have greatly benefited the field of prosthetics in the last few years. Today’s prosthetic limbs are made using space-age materials that provide increased durability and function. In addition, many prosthetics make use of bionic technology. These types of prosthetics are called myoelectric prosthetics.

Let’s Take Your Data Dreams to the Next Level

Myoelectric prosthetics picks up the electrical action potential from the residual muscles in the amputated limb. Upon receiving the action potentials, the prosthetic amplifies the signal using a rechargeable battery. Detected signal can be used further into usable information to drive a control system. Artificial Intelligence helps to identify motion commands for the control of a prosthetic arm by evidence accumulation. It is able to accommodate inter-individual differences and requires little computing time in the pattern recognition. This allows more freedom and doesn’t require the person to perform frequent, strenuous muscle contractions. The inclusion of AI technology in prosthetics has helped thousands of amputees return to daily activities. While technologies that make bionic implants possible are still in infancy stage, many bionic items already exist.

The Bionic Woman

 Angel Giuffria is an amputee actress and Ottobock Healthcare’s Brand Champion who has been wearing electromechanical devices since she was four months old. Following are excerpts of an interview with her.

“I wear currently the bebionic 3 small-size hand which sounds like a car. But at this point, that’s where we’re getting with technology. It’s a multi-articulating device. That small-size hand is really amazing… this technology wasn’t available to them previously”

She further added, “..The new designs that look more tech are able to showcase the technology. I’ve really become attached to and I think a lot of other people have really clung onto as well because it just gives off the impression of showing people how capable we are in society now.”

 She also spoke about prosthetics like the Michelangelo Hand which is stronger, faster and has multiple hook options. Modern additions to prosthetics such as lights and cameras are added advantages. She describes her hand to be able to do multiple functions like change grip patterns and control wrist movements which enable her to hold small items like keys and credit cards.

angelgiuffriaottobokbebionichand

I-limb

Bertolt Meyer’s amazing bionic hand controlled via an iPhone app is another glimpse at the advances being made in prosthetics.

In 2009, Meyer, a social psychologist at the University of Zurich was fitted with an i-limb, a state-of-the-art bionic prosthesis developed by a Scottish company, Touch Bionics, which comes with an aluminum chassis and 24 different grip patterns. To select a new suite of gestures, Meyer simply taps an app on his iPhone. He describes his i-limb to be the first, where aesthetics match engineering.

Bertolt-Meyer-who-has-an--010

In the world of prosthetics, function is the key. Most amputees are constantly searching for the same level of functionality that they enjoyed before they lost their limb. With the introduction of artificial intelligence in prosthetic limbs, amputees are closer to their goals than ever before. Bionics having access to the relevant databases are capable of learning new things in a programmed manner which improves their performance.

For more such interesting blogs follow Dexlab Analytics. Also take a look at the Machine Learning courses being offered by Dexlab Analytics– a premier analytics training institute in Gurgaon.

 

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Reigning the Markets: 4 Most Influential Analytics Leaders of 2018

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Data analytics in India is grabbing attention. Data and analytics, together, they play a key role in delivering business opinions, which are high-yielding and relatively new. At the helm of such robust data analytics growth are leaders from numerous organizations who introspect into data to conjure up decisions as a seamlessly as possible. They are masterminds in the world of data analytics.

Reigning the Markets: 4 Most Influential Analytics Leaders of 2018

Here, we will talk about 4 most influential analytics leaders who acted as pioneers of bringing in newer technologies and life-changing innovations into the field of analytics, machine learning, artificial intelligence and big data across diverse domains.

Debashish Banerjee, Managing Director, Deloitte Analytics

With 17 years and more experience in predictive modeling, data analytics and data science, Mr. Banerjee’s extensive contribution in the fields of actuarial risk, data mining, advanced analytics and predictive modeling in particular is phenomenal. He started his career with GE, and initiated and headed insurance analytics, pricing and reserving team of GE, India – one of the firsts in India.

In 2005, he shifted to Deloitte with a mission to initiate the advanced analytics and modeling practice in India, through which he manages and offers leadership support to the Deloitte Consulting’s Data Science practices that stresses on AI, predictive modeling, big data and cognitive intelligence. He mostly worked in marketing, customer and HR domains.

Let’s Take Your Data Dreams to the Next Level

Kaushik Mitra, Chief Data Officer and Head of Big Data & Digital Analytics, AXA Business Services (ABS)

Experienced for over 25 years in integrating analytics, technology and marketing worldwide, Kaushik Mitra dons a lot many hats. Besides assuming leadership roles for diverse domains, like AI, analytics, data science, business intelligence and modeling, Mr. Mitra is at present involved in driving an array of data innovation coupled with technology restructuring in the enterprise, as well as coordinating GDPR implementation in ABS.

Before joining ABS, he worked with Fidelity Investments in Bangalore, where he played a pivotal role in establishing their data science practice. Armed with a doctorate in Marketing from the US, he is a notable figure in the world of analytics and marketing, along with being a frequent speaker in Indian industry networks, like NASSCOM and other business forums.

Ravi Vijayaraghavan, Vice President, Flipkart

Currently, Ravi Vijayaraghavan and his team are working on how to leverage analytics, data and science to improve decision-making capabilities and influence businesses across diverse areas within Flipkart. Before joining Flipkart, he used to work as Chief Data Scientist and Global Head of the Analytics and Data Sciences Organization at [24]7.ai. It was here that he created, developed, implemented and optimized machine learning and analytics driven solutions. Also, he held important leadership portfolios at Mu Sigma and Ford Motor Company.

Deep Thomas, Chief Data & Analytics Officer, Aditya Birla Group

“Delivering nothing but sustained and rising profitability figures through potent digital transformation and leveraging data, business analytics, multi-disciplinary talent pool and innovative processes” – has been the work mantra of Deep for more than two decades. Being the Chief Data & Analytics Officer for Aditya Birla Group, he spearheads top of the line analytics solutions and frames organization-wide initiatives and tech-induced programs to enhance business growth, efficiencies and productivity within an organization.

Initially, he headed Tata Insights and Quants, the much acclaimed Tata Group’s Big Data and Decision Science Company. Apart from this, he held a variety of leadership positions in MNCs like Citigroup, HSBC and American Express across US and India to boost global digital and business transformation.

This article has been sourced from – https://analyticsindiamag.com/10-most-influential-analytics-leaders-in-india-2018

For more such interesting blogs and updates, follow DexLab Analytics. It’s a premier data science certification institute in Delhi catering to data aspirants. Take a look at their data science courses in Delhi: they are program-centric and nicely curated.

 

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Risk Analytics: How to Frame Smarter Insights with Organizational Data

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Companies are launching cloud-based data analytics solutions with an aim to aid banks improve and manage their risk efficiently and streamline other activities in the most cost-effective ways.

Risk Analytics: How to Frame Smarter Insights with Organizational Data

Risk analysis is a major constituent of banking circle. Analytics-intensive operations are being run in almost all banking institutions, including cyber-security, online data theft and third-party management. The concept of risk is not something new. For years, it has been the key responsibility of C-suite professionals, but the extravagant amount of awareness and recognition associated with risk analytics was missing then. Also, the regulatory and economic landscape of the world is changing and becoming more intense – hence, risks need to be managed adequately. The executive teams should make risk analytics their topmost agenda for better organization functioning.

Why risk analytics?

The first and foremost reason to incorporate risk analytics is to measure, quantify and forecast risk with amped certainty. Analytics help in developing a baseline for risk assessment in an organization by working on several dimensions of risk and pulling them in a single unified system for better results.

What are the potential benefits of risk analytics?

  • Risk analytics help in turning guesswork into meaningful insights by using a number of tools and techniques to draw perspectives, determine calculable scenarios and predict likely-to-happen events.

  • An organization stay exposed to risk. Why? Because of a pool of structured and unstructured data, including social media, blogs, websites available on both internal and external platforms. With risk analytics, you can integrate all these data into a single perspective offering actionable insights.

  • Risk is a largely encompassing concept, spilling across several domains of organizational structure that at times it can really be hard to know how to manage risk and pull out meaningful insights. In such situations, risk analytics play a pivotal role in ensuring organizations develop foresight for potential risks and provide answers to difficult questions so as to create a pathway for action.

Things to do now:

Ask the right questions

Analytics means research. It ushers you to ask questions and dig deeper into risk-related stuffs. But framing random questions don’t help. To have a real impact, conjure up a handful of questions that hits the real topic.

Understand interdependencies

Risk pierces into organizational boundaries. And analytics work by offering cross-enterprise insights, by inferring conclusions throughout the business. That makes it effective to tackle far-reaching issues.

Streamline productive programs

Analytics help decision-makers introspect and evaluate risks, as well as rewards – related to operational and strategic decisions. Adding insights into pre-determined actions to determine and curb risks yield sustainable value for the program, which in the end improves overall program performance.

Let’s Take Your Data Dreams to the Next Level

In the end, risk analytics seem to be quite a daunting subject to take up, but the truth is, some organizations are really doing well in managing their risks. If you are frustrated somehow and this whole concept of risk analytics baffles you more, take up SAS risk management certification. DexLab Analytics, a premier market risk training institute offers incredible market risk courses for data-hungry aspirants.

 

The article has been sourced from – https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Deloitte-Analytics/dttl-analytics-us-da-oriskanalytics3minguide.pdf

 

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How India is driving towards Data Governance

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Data is power – it’s the quintessential key to proper planning, governance, policy decisions and empowering communities. In the recent times, technological expansion is found to be contributing immensely towards ensuring a sustainable future and building promising IT base. Robust developments in IT related services have resulted into key breakthroughs, including Big Data, which as a result have triggered smooth data governance.

How India is driving towards Data Governance

According to a NASSCOM report, India’s analytics market is expected to grow from $1 billion to $2.3 billion in the year 2017-18. However, the fuller benefits of data analytics are yet to be channelized by the public sector.

In a varied country like India, data collection is a lengthy procedure. At present, information is being collected by various government departments straight from Panchayat levels to state levels. Though, most of the data remains trapped within department walls, it is largely used to pan out performance reports. Also, certain issues in timely collection of data pops up, while sometimes the quality of data collected becomes questionable, hence delaying the entire analysis.

 

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Quality data plays an integral role, if analyzed properly at the proper time. They can be crucial for decision-making, delivery of services and important policy revisions. As a matter of fact, last year, Comptroller and Auditor General (CAG) initiated Centre for Data Management and Analytics (CDMA) to combine and incorporate relevant data for the purpose of auditing. The main purpose here is to exploit the data available in government archives to build a more formidable and powerful Indian audit and accounts department.

Indian government is taking several steps to utilize the power of data – Digital India and Smart Cities initiatives aim to employ data for designing, planning, managing, implementing and governing programs for a better, digital India. Many experts are of the opinion that government reforms would best work if they are properly synchronized with data to determine the impact of services, take better decisions, boost monitoring programmes and improve system performances.

Open Data Policy is the need of the hour. Our government is working towards it, under the jurisdiction of the Department of Information and Technology (DIT) to boost the perks of sharing information across departments and ministries. Harnessing data eases out the load amongst the team members, while ensuring better accountability.

Tech startups and companies that probe into data and looks for solutions in data hoarding and analytics to collect and manage complicated data streams need to be supported. The government along with local players should encourage citizens to help them in collecting adequate information that could help them in long-run. India is walking towards a rapid economic development phase, where commitment towards information technology, data governance and open-source data is of prime importance. For the overall economy, bulk investments in capacity building, technology implementation and data-facilitating structures should be considered and implementable to bring plans and participation into place to hit off a better tech-inspired reality.

For data analyst certification in Delhi NCR, drop by DexLab Analytics – it’s a prime data science online training centre situated in the heart of Delhi.

The original article appeared on – https://economictimes.indiatimes.com/small-biz/security-tech/technology/indias-investment-in-big-data-will-ensure-governance/articleshow/57960046.cms

 

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New Intelligence is being added to Massive Storage Management System

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Pioneers of High Performance Storage System (HPSS) are devising ways to streamline and rationalize data management products for its upcoming eighth generation. 25 years back, US Department of Energy research laboratories and IBM together built HPSS to support massive government science research projects. Why? The Hierarchical storage solution is undeniably a rewarding concept which uses organization policies and software automatic tricks to decide which data to save, the location where it should be saved, the best time to move it to different storage devices and when to delete it.

New Intelligence is being added to Massive Storage Management System

“How do you know what you’re archiving? We’re talking about archives now that are hundreds of petabytes to an exabyte. We think we’re going to be there in 2-3 years,” asked Todd Herr, a storage architect for supercomputing from Lawrence Livermore National Laboratory, CA.

The HPSS website catalogues 37 publicly disclosed customers, while other customers are kept discreet. At present, version 7.5.1 from last year is on the run, but version 7.5.2 might be hit, while the next year will see 7.5.3, as given in the online roadmap.

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However, version 8 is not yet available on the official roadmap, but here’s what the insiders have to say about it…

“What I think our challenge is, is to become good data curators. And I think that’s where we’re going to point the product,” Herr shared. This will turn HPSS become more capable for data mining and assign metadata to itself.

In order to do that, the first thing to be done is to reveal information in the archive about a few overarching namespace applications. Herr explained, “Right now we are working on that (referring to software made by companies such as Atempo, Robinhood, Starfish, and StrongLink). I think the next step there is scaling out metadata performance, such as database partitioning and virtualizing multiple processors when performing searches.”

Another important part of HPSS is related to the software that works with tape storage – “What we’re trying to do is enable fast access to tape. If you look across the industry spectrum, the words fast and tape generally don’t go together,” Herr intimidated. The scientists at Livermore are capable of accessing research data on tape, even that existed more than 50 years ago.

Speed-matching buffers can save the day – when placed between primary disk storage and archive tape storage, they can be used to both read and write. Some other physical improvements include faster head placements and tape motors.

“We’re going to hit a problem way faster than most sites, and certainly faster than the vendors themselves because they cannot replicate our environment in most testing,” Herr asserted.

Herr’s employer’s next supercomputer, Sierra is going to operate at up to 125 petaflops and will have a 125-petabyte file system for performing ample tests to find new ways of speeding up performance and administer advanced data storage mechanisms.

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The article has been sourced from – https://www.techrepublic.com/article/fed-and-ibm-researchers-adding-new-intelligence-to-massive-storage-management-system

For more such interesting ideas and discussions, stay tuned to DexLab Analytics. It is a premier analytics training institute headquartered in Delhi, NCR. Their data science certification courses are excellent.

 

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Watch Out: Top Retail Trends 2018 That Might Redefine Industry Goals

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They must change – retailers finally understood this basic but true fact. For years, the retail honchos were averse to change – they preferred everything to be smooth and consistent like they were in previous years.

Watch Out: Top Retail Trends 2018 That Might Redefine Industry Goals

Now, the retail game-play is changing altogether. Today, it’s the customer who defines the entire shopping experience. No longer, storing data in traditional silos is termed as a viable option – the integration of omni-channel trade and tech-inspired merchandizing is the go-to option. Already, several well-funded retailers and global store giants are on their way to exploit the data power – they are adjusting their working mechanisms and resorting to assortment and innovations because that’s the only way to survive and sail away!

Looking ahead, here are some of the biggest retail trends to watch in 2018:

A dramatic evolution in technology

Technological transformation holds a fresh can of possibilities for retailers, but its implementation demands a lot of attention. While 2017 was reckoned to be the year of digital discovery, 2018 is going to be the year when retailers will adapt with the changing market and experience evolution in their customer’s needs. Hence, evolution will be the key to success.

Opportunities in AI are also on the rise. Chatbots, robotics and facial recognition and image recognition technologies are unleashing robust opportunities this year. Retailers are hoarding large chunks of data to curate personalized experiences for customers, and win their hearts away. More data means improved algorithm performance, and the best thing is that retailers are going on generating significant amounts of data, through both offline and online mediums. Artificial intelligence in retail can be utilized in many ways, right from improving product specifications and enhancing customer service experience.

Artificial intelligence coupled with machine learning and Internet of Things supports customer experience – there exists amazing opportunity for retailers to gain by using these new age concepts. For better data utilization, get yourself an excellent data analyst training from DexLab Analytics.

Mobile payments will usher us into a cashless economy

China has already gone cashless; thanks to AliPay and WeChat Pay. Following that, the rest of the world is looking up to the likes of Amazon Pay, Walmart Pay, Apple Pay and other types of cryptocurrencies. It’s only a matter of time before global consumers replace their plastic debit cards with more efficient and faster mobile payment options.

Work on improving offline experiences too

Not only online, but retailers should consider looking into offline experiences – how they can keep shopping as human, real and visual as possible. The mode of shopping might be transforming, but humans and their preferences are still the same. Customer experience is still important and offline experience will just focus on that.

Robotic retail is scaling up

In the E-commerce industry, the robot to human ratio is fast changing. While Walmart is testing retail robots, drone delivery is increasingly becoming popular and a viable solution. By 2020, its predicted consumer facing robots will show up in retail stores, all over.

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Improvements in technology mean a lot of retail growth. And when its technology, we can’t leave behind DATA. It’s like the new currency in the retail scenario – for a comprehensive Retail Analytics Courses, visit DexLab Analytics.

The article has been sourced from:

https://www.forbes.com/sites/pamdanziger/2017/12/27/retail-shopping-predictions-2018/#1116fcdafb33

 

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