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Getting Started with Machine Learning: Crack the Code

Getting Started with Machine Learning: Crack the Code

Machine Learning has taken us all to the tipping point from where the entire ballgame of technology and the way we interact with the digital world has started changing and the surge is expected to continue over the next decade. Increasingly, the decisions of the future are going to be made by machines, and we can’t seem to be more excited!!

It’s time to adopt Machine Learning

According to McKinsey reports, AI adoption in the tech sector is at its nascent stage, with few firms implementing it on a large scale. The companies that are yet to deploy it are still in two minds whether they should expect return on investments or not.

Nevertheless, skilled data scientists better be start speeding up the process of implementation of these emerging technologies if they want to stay right on edge ahead of their tailing rivals. Machine Learning is the new in-thing that must be embarked on RN.

And for that, here goes the following tips that will help you ride towards AI success:

Inspect the areas where data science fits into

Leverage data science and Machine Learning within an organization to trigger better optimization and smoother implementation. Imbed data science and machine learning into every department, like HR, marketing, sales and finance. Also, try pairing data scientists with software engineers to build agile models on machine learning, that’s the best way to scale across company operations better.

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Treat data as money

Today, data acts as the fuel for an organization. But it can also be treated as money, and diligent data consultants need to manage, protect and obsess over it. Data is powerful but in order to derive the best out of it, it needs to be played well in the hands of experts. And those hands are of data specialists who values data like money.

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Stop hunting down purple squirrels

No wonder, data scientists are individuals with an exceptionally high aptitude in math and statistics; they are skilled in evaluating insights in data. They don’t necessarily have to be software engineers who only know how to write algorithms and curate tech products. Data scientists are much more than that.

Companies often seek unicorn-like aspirants who are ninja software engineers, ace statisticians and master of industry domain, but the sad part is that they look for all these 3 character traits in a single job candidate, which needs to be changed.

Keep an eye on ‘derived data’

If you are thinking of sharing your algorithms with any other person then the chances are high that they will see your data. But companies that are keen on protecting its data should refrain from such activities. Data for informatics companies is like a new currency – they need to be well-guarded and treasured for life!

Educate about the perks of AI

AI is a blessing, for all you tech nerds and gizmo jerks. And accomplished data professionals should look for ways to promote AI and influence friends and co-workers to embrace this new king-some technology. After all, successful machine learning implementation may become the key to your company’s future growth, provided you treat it in the right manner.

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IoT is Advancing but without Enough Security: What You Need to Do

IoT is Advancing but without Enough Security: What You Need to Do

IoT is eminent. And a wide number of nerdy IT specialists are scared as hell.

A recent survey pointed that 78% of IT decision makers accepted that they are skeptical if their business lose crucial data enabled by IoT devices. Amongst them, 72% even said the speed at which IoT adoption is gaining ground is worrisome because they are yet to evolve necessary security arrangements.

As the saying goes, there’s no smoke without fire – the recent WannaCry Ransomware is the best example to point out security issues related to IoT– it infringed and crippled Bank of China’s ATM networks and washing machine networks. In another instance, a company that looked after much of the Internet’s domain name structure was brought down by using somewhat 100,000 “malicious endpoints” from IoT devices. All owing to security lapses in the adoption of IoT infrastructure.

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The notion is that IoT is still largely under-secured and poses larger than life security threats and risks as companies are trusting suave IoT devices for some way or the other, as a result jeopardizing their own operational, profitability and safety decisions.

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AI is the Answer!!

AI can come to the rescue, whenever security of IoT is the concerning matter. Proponents defend saying machine learning can easily identify usage patterns and send signals to the system, whenever abnormalities are recorded or even occur. Reason: all the IoT devices are limited in function, so it becomes easier to recognize irregularities.

Again, a combination of everything is never a bad idea. Undoubtedly, AI plays a prominent role in uplifting IoT security, but a comprehensive IoT solution would include an amalgamation of everything, like AI, government regulation and standards.

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Though the ever-so-increasing tech industry is capable of devising an effective solution, but the real deal in here is to perform everything on a breakneck timetable. At present, in between IoT security and IoT adoption, the latter is winning.

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Here’s a set of suggestions that helps in latching on with the IoT without compromising on the security part:

  • Implement an integrated approach – Anytime, more is better. The companies that are relying on IoT should seek to integrate management solutions and welcome a powerful IoT framework to boost smooth data movement and good connectivity that pulls in data into a robust analytical environment, which is albeit more sophisticated and makes room for flawless behavioral analysis, which is automated – “by integrating those components, you can be more confident that what you’ve got from a feed in an IoT environment is more statistically valid,” Chris Moyer, CTO and VP-cybersecurity at DXC said.
  • Choose the perfect IoT devices – Formidable ecosystem and having a series of companions that shows no inhibitions in the manner they share information stems out to be the right IoT devices.
  • Look forward to Edge Devices and IoT Gateways – To counter the lack of security measures, top of the line companies are using Edge Devices and IoT Gateways to bind more impregnable layers of protection between insecure equipments and the internet.
  • Go create standards – From a macro level perspective, you should ensure a 360-degree IoT security for the next few years and that is only possible if you start setting standards in your business as well as in tech from now on.

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AI-Smart Assistants: A New Tech Revolution in the Make

2018 has begun. And this year is going to witness a mega revolution in the field of technology – the rise of AI-powered digital assistants. Striking improvements in key technologies, like natural language processing and voice recognition are making smart assistants more productive, helping us use electronic devices just by interacting with them.

 
AI-Smart Assistants: A New Tech Revolution in the Make
 

Smart voice assistants are going mainstream. From Apple’s Siri to Google’s Assistant to Samsung’s Bixby, superior digital assistants are on a quest to make our lives easier, while taking us a step closer to a world where each one of us will have our own personal, 24/7 –all-ears AI assistants to fulfill our every wish and command.

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The Future of Technology is Here: 3 Tech Categories That Will Rule in 2018

The Future of Technology is Here: 3 Tech Categories That Will Rule in 2018

No organization can survive without – technology. It has seeped into our lives for good, and is further predicted to expand its horizons across multiple sectors in the next couple of years. The forecasters has even predicted that 4% more would be spent on purchasing software, technology and hardware by government bodies and corporations, as well.

Now, this kind of growth and development will push the global tech industry to hit the $3 trillion mark. But amidst all this startling stats and discoveries, what still remains under the clouds is the fact how to decide which technology to invest in – or whether you should invest at all.

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Communication

Communication technology is crucial. It is more important for startups, where employees work remotely, as highlighted by a leading daily. In fact communication platforms offer a gamut of benefits, right from increased productivity to form superior teams and ability to nurture better company cultures. Furthermore, these technologies in the end help entrepreneurs monitor budget closely, which is enough to point out why strong communication is fruitful.

Cutting edge messaging services like HipChat and Slack ensures better communication networking for employees working outside the office. On the other hand, fantastic tools like Basecamp streamlines operations irrespective of the location of staffs, while LinkedIn and Ripple ensures better connectivity on a more personal level.

Artificial Intelligence

AI is a must-have technology tool for every organization coming up this year and ahead, because this field of science is expanding very rapidly. A lot of new discoveries and innovations are taking place around AI, and you need to be ahead of the curve. As more and more data gets churned out, deep-learning techniques starts to gain momentum, which tends to evolve the pattern of data analysis.

On this note, Google Home and Amazon Alexa launched their own virtual assistant – though the ability to interact with devices was in existence for quite some time now, these masterminds gave a push to this technology a little more.

Similarly, it’s been revealed in a McKinsey report that around 45% of work activities are going to be automated, thanks to the power of AI.

Blockchain Technology

Much more than just performing financial transactions, blockchain technology is a bright beacon of hope for all tech freaks. Though this technology was in active phase, it’s enjoying heyday now. Market Reports Hub predicts that this market will exceed $2 billion by 2021, and that definitely calls for a celebration!

The main objective of blockchain is to nurture and enhance the trust between enterprises. Though in the beginning, startups and entrepreneurs may feel a little bit intimidated to implement this new-age, ultra-famous tool of technology in their organization but later on they can’t thank more! Right from navigating through sales, finances, marketing, communication and creativity, Blockchain is a sure-fire way to make this New Year a booming success.

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The More, The Better: Why Focus on More Than One Coding Language for Better Developer Jobs?

The More, The Better: Why Focus on More Than One Coding Language for Better Developer Jobs?

Attention all you developers: Be versatile, be ahead of the curve.

Excelling over just one programming language won’t do any good, and will restrict your career pathway. On closer inspection, you’d find that the top 25 Forbes listed companies never rely on a single coding language for their products and services – instead they prefer on applying at least 4 different languages to always be on edge.

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5G Mobile Innovation: 3 Key Takeaways That Every Business Leader Should Know About

5G stands for fifth generation wireless connectivity based on the IEEE 802.11ac standard of broadband technology, though an official standard is yet to be fixed. It comes with a lot of promises – better bandwidth, faster speed and lower latency that affects (positively) customers and businesses, as well.

5G Mobile Innovation: 3 Key Takeaways That Every Business Leader Should Know About

Although it isn’t expected to roll out until 2020, a large number of companies have already started prepping up to adopt and incorporate 5G mobile connectivity into their business scopes and operations. As the biggest shift in technology is looming right ahead, business leaders around the world are leaving no stone unturned to fathom the rich impact of 5G on several next-gen techs, like self-driving cars and cloud computing.

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Here’s Why Indian Techies Need to Imbibe Rich AI and Data Science Skills to Ride High This 2018

Here’s Why Indian Techies Need to Imbibe Rich AI and Data Science Skills to Ride High This 2018

Amid growing anxiety over machines replacing human intelligence, Indian IT sector is seeking out expert skills in new technologies, involving big data, artificial intelligence and machine learning. There exists a high demand for skills in such newer streams of technology, which now forms the backbone of businesses. It’s not like these jobs appeared out of thin air; after being labeled as “niche skills” for several years, they are now making their way into the mainstream industry. 

This year, this trend is going to gain more momentum. It is expected to create 180000 to 200000 new jobs in 2018, mostly related to these new technologies – Alka Dhingra, the general manager of IT staffing at TeamLease Services, stated. It is equally applicable for both large service organizations as well as budding startups.

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The Hot-List:

Here’re the notable areas, where job creation will hit in 2018:

Artificial Intelligence

Almost all Indian IT bigwigs are going gaga over AI. TCS, Infosys, Flipkart – nearly all native companies have started delving deeper into data to scale up their business operations and secure success in the future.

Though the world is being ruled by MACHINES, at the same time it’s HUMANS who train machines the way they function to perform human-like tasks. For that reason, the country’s IT unicorn, Tata Consultancy Services has trained more than 200000 employees about IoT and AI. Also, last month, India’s e-commerce giant, Flipkart launched an AI-inspired initiative known as AI for India, through which it has planned to leverage all the data it has gathered over the last few years to frame robust AI-driven solutions that will boost their operational activities further. Millions of dollars are being invested in this program – a company representative shared.

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Data Science

For several years, native internet companies have been accumulating massive consumer data, which they now plan to mine it to their best interests. Just like Flipkart’s AI for India initiative, food-delivery-tech startup Swiggy is also working hard on its consumer data so that it can start making deliveries even more efficient and faster.

Some HR experts say that pharmacy analytics – an amalgamation of healthcare and analytics will also generate several new jobs for data scientists this new year– at present, machine learning, data analytics and data scientists’ jobs are the most searched jobs on all leading job portals in India.

Blockchain Technology

While bitcoin and cryptocurrency takes the world by storm, top-notch market specialists predict this advanced field of technology is going to create an exploding number of jobs. Cryptocurrency has already started drawing in a large pool of Indian investors, and legal experts are now asking for regulations.

“There could be regulations (for bitcoin) coming, and hence somebody who knows the subject is going to be in demand,” Aditya Narayan Mishra, CEO of CIEL HR Services, said.

Digital Marketing

Digital technologies are now omnipotent. All startups and matured companies across every domain are adopting suave digital solutions for various functions, like HR, manufacturing, operations, warehousing and communications. In the same manner, marketing too is not limited to its erstwhile conventional mediums; digital marketing is the new talk of the town.

“With more companies in India wanting to increase their digital presence, there is a visible surge in job searches for digital marketing jobs,” Sashi Kumar, the managing director of jobs portal Indeed India, said.

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Stories of Success: Molecular Modeling Toolkit (MMTK), Open Source Python Library

Stories of Success: Molecular Modeling Toolkit (MMTK), Open Source Python Library

Welcome again!! We are back here to take up another thrilling topic and dissect it inside out to see what compelling contents are hidden within. And this time we will take up our newly launched Python Programming Training Module – Python, invented by Guido Van Rossum is a very simple, well-interpreted and goal-specific intensive programming language.

Programmers love Python. Since there is zero compilation step, debugging Python programs is a mean feat. In this blog, we will chew over The Molecular Modeling Toolkit (MMTK) – it’s an open source Python library for molecular modeling and simulation. Composed of Python and C, MMTK eyes on bio-molecular systems with its conventional standard techniques and schemes, like Molecular Dynamics coupled with new techniques based on a platform of low-level operations.

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It was 1996, when the officials from Python Org, including Konrad Hinsen (He was then involved in the Numerical Python project, but currently working as a researcher in theoretical physics at the French Centre National de la Recherche Scientifique (CNRS). He is also the author of ScientificPython, a general-purpose library of scientific Python code) started developing MMTK. They initially had a brush off with mainstream simulation packages for biomolecules penned down by Fortran, but those packages were too clumsy to implement and especially modify and extend. In order to develop MMTK, modifiability was a crucial criterion undoubtedly and they gave it utmost attention.

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The language chosen

The selection of language took time. The combination of Python and C was an intuitive decision. The pundits of Python were convinced that only a concoction of a high-level interpreted language and a CPU-efficient compiled language could serve their purpose well, and nothing short of that.

For the high-level segment, Tcl was rejected because it won’t be able to tackle such complex data structures of MMTK. Perl was also turned down because it was made of unfriendly syntax and an ugly integrated OO mechanism. Contrary to this, Python ranked high in terms of library support, readability, OO support and integration with other compiled languages. On top of that, numerical Python was just released during that time and it turned out to be a go-to option.

Now, for the low-level segment, Fortran 77 was turned down owing to its ancient character, portability issues and low quality memory management. Next, C++ was considered, but finally it was also rejected because of portability issues between compilers in those days.

 

The architecture of library

The entire architecture of MMTK is Python-centric. For any user, it will exude the vibes of a pure Python library. Numerical Python, LAPACK, and the netCDF library functions are observed extensively throughout MMTK. Also, MMTK offers multi-threading support for MPI-based parallelization for distributed memory machines and shared memory parallel machines.

The most important constituent of MMTK is a bundle of classes that identify atoms and molecules and control a database of fragments and molecules. Take a note – biomolecules (mostly RNA, DNA and proteins) are administered by subclasses of the generic Molecule class.

Extendibility and modularity are two pillars on which Python MMTK model is based. Without going under any modification of MMTK code, several energy terms, data type specializations and algorithms can be added anytime. Because, the design element of MMTK is that of a library, and not some close program, making it easier to run applications.

Note Bene: MMTK at present includes 18,000 lines of Python code, 12,000 lines of hand-written C code, and several machine-generated C codes. Most of the codes were formulated by one person during eight years as part of a research activity. The user community provided two modules, few functions and many ideas.

For more information, peruse through Python Training Courses Noida, offered by DexLab Analytics Delhi. They are affordable, as well as program-centric.

 

This article is sourced from – www.python.org/about/success/mmtk

 

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Google is Back in China! It Decides to Open an AI Lab in the Far-East

Google is Back in China! It Decides to Open an AI Lab in the Far-East

 

Google is strengthening its artificial intelligence base, including China.

 

And it is so doing by establishing a new AI research center in Beijing. Google is digging deep into China, where it contravened the government in 2010 committing a spectacularly principled act of self-sabotage by refusing to self-censor search content and later found most of its services to be blocked. The company’s decision to return back to China is more about safeguarding its future, and acknowledging the supreme importance of technology’s most competitive field: AI.

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