Tech Education

Tech Education is a versatile blog on various technology. It provides best knowledge about technical education with reference.

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Best Data Analytics Consulting | Training | Staffing - Emerging India Group

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Emerging India Group provide the best data analytics training in Noida. We are also in Data Analytics Consultancy and Staffing. Conatct Us Now. nasscom certified.

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Emerging India Group provide the best data analytics training in Noida. We are also in Data Analytics Consultancy and Staffing. Conatct Us Now

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Emerging India Group provide the best data analytics training in Noida. We are also in Data Analytics Consultancy and Staffing. Conatct Us Now

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Deep Learning Data Analytics

Deep Learning is the foundation of some latest advancements in AI and Robotics. Create your own deep learning algorithm to perform some fascinating tasks like image classification with the help of sensor flow and Keras libraries.

This article is part of Demystifying AI, a series of posts that (try to) disambiguate the jargon and myths surrounding AI.

Around 2012, researchers at the University of Toronto used deep learning for the first time to win ImageNet, a popular computer image recognition competition, beating the best technique by a large margin. For those involved in the AI industry, this was a big deal, because computer vision, the discipline of enabling computers to understand the context of images, is one of the most challenging areas of artificial intelligence.

And naturally, like any other technology that creates a huge impact, deep learning became the focus of a hype cycle. Subsequently, deep learning pushed itself into the spotlight as the latest revolution in the artificial intelligence industry, and different companies and organizations started applying it to solve different problems (or pretend to apply it). Many companies started rebranding their products and services as using deep learning and advanced artificial intelligence. Others tried to use deep learning to solve problems that were beyond its scope.

Meanwhile, media outlets often wrote stories about AI and deep learning that were misinformed and were written by people who did not have proper understanding of how the technology works. Other, less reputable outlets used sensational headlines about AI to gather views and maximize ad profit. These too contributed to the hype surrounding deep learning.

And like every other hyped concept, deep learning faced a backlash. Six years later, Many experts believe that deep learning is overhyped, and it will eventually subside and possibly lead to another AI winter, a period where interest and funding in artificial intelligence will see a considerable decline.

Other prominent experts admit that deep learning has hit a wall, and this includes some of the researchers who were among the pioneers of deep learning and were involved in some of the most important achievements of the field.

But according to famous data scientist and deep learning researcher Jeremy Howard, the “deep learning is overhyped” argument is a bit— well—overhyped. Howard is the founder of fast.ai, a non-profit online deep learning course, and he has lots of experience teaching AI to people who do not have a heavy background in computer science.

Howard debunked many of the arguments that are being raised against deep learning in a speech he delivered at the USENIX Enigma Conference earlier this year. The entire video clarifies very well what exactly deep learning does and doesn’t do and helps you get a clear picture of what to expect from the field.

Here are a few key myths that Howard debunks.

Deep learning is just a fad—next year it’ll be something else

Many people think that deep learning has popped out of nowhere, and just as fast as it has appeared, it will go away.

“What you’re actually seeing in deep learning today is the result of decades of research, and those decades of research are finally getting to the point of actually giving state of the art results,” Howard explains.

The concept of artificial neural networks, the main component of deep learning algorithms, have existed for decades. The first neural network dates to the 1950s.

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Data Scientist

Masters Program

This Master’s Program provides training in the skills required to become a certified data scientist. You’ll learn the most in-demand technologies such as Data Science on R, SAS, Python, Big Data on Hadoop and implement concepts such as data exploration, regression models, hypothesis testing, Hadoop, and Spark.

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Machine Learning consulting

The numbers are encouraging. According to an assessment by the Associated Chambers of Commerce and Industry of India (Assocham), management consulting is expected to grow at a compounded annual growth rate of 30 percent to become an Rs 27,000-crore industry by 2020. However, with the advent of advanced and newer technologies, management consultants have challenges to tackle. The challenges represent just one side of the door. The other side holds opportunities.

Here is a walk through the challenges and opportunities that consulting firms are already facing and will continue to face in 2019.

The startup invasion

The rapidly emerging trends have given birth to a large number of new startups in the consulting industry. And they know very well, where to tap and how to deliver best. They are players who are adept at creating solutions through proper use of data analytics, cloud services, cognitive computing and many other advances that are bringing transition.

These newbies come with a deep understanding of such new technologies and know how to adopt them faster in order to deliver better results to their clients. The existing firms should learn from them. For them, it’s both a challenge and opportunity.

The digital outburst

Digital is taking every sector by storm.

Consulting is no different. With emerging technologies like AI, machine learning and Big Data, it has become crucial for management consultants to adopt these technologies for delivering quick solutions to sporadic issues faced by their clients. On the other hand, these technologies are also opportunities for consultants and consulting firms to come out with the best innovative solutions.

Adopting such tech changes will not only save time but also help consultants deliver apt solutions instantly.

The gig economy

Today’s professionals are very comfortable in the freelancing eco-system, where they work with various clients on a contract or project basis. Although this kind of job doesn’t provide specific benefits, for instance, pension scheme or paid leave as compared to a permanent salaried job, freshers still prefer such roles for the freedom and other benefits they offer. Here, you can work from home. And when it comes to consulting firms, gig economy has emerged as one of the best platforms to tap into the right talent. This is again an opportunity and challenge. Here is the challenge: there have been cases of consulting firms having to spend considerable time on training such freelance professionals, followed by other issues like data theft or misuse of paid tools given by the consulting firm to the freelance employee.

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Data Science vs. Big Data vs. Data Analytics

Source: www.simplilearn.com