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10 Best Online and Free Deep Learning Courses

10 best online and free deep learning courses

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While deep learning is viewed as a small part of the field of artificial intelligence, it’s now a field that is by all accounts growing out of the AI space itself. Deep learning is the advancement of ‘thinking’ computer systems, called neural networks, and using it requires coding procedures unfamiliar to old-school developers. With the assistance of deep learning, we can show our computers to learn for themselves such that it gives us noteworthy outcomes. Furthermore, you get the opportunity to be at the front line, as experts in profound learning are required now like never before.
If you want to learn deep learning and don’t know where to start, we’ve compiled a list of free online courses that can help you learn deep learning.

This course covers the essential segments of deep learning. What it implies, how it works, and creating necessary code to build different algorithms, for example, deep convolutional networks, variational autoencoders, generative adversarial networks, and recurrent neural networks. A significant offering of this course will be to not just see how to build the fundamental segments of these algorithms, yet in addition how to apply them for exploring creative applications. Free and paid …

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Vision Processing Unit Market- Roadmap for Recovery from COVID-19|Growing Adoption of Deep Learning and AI to boost the Market Growth | Technavio

vision processing unit market- roadmap for recovery from covid-19|growing adoption of deep learning and ai to boost the market growth | technavio

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The Global Vision Processing Unit Market will grow by USD 892.45 mn during 2020-2024

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MarqVision detects counterfeit products with deep learning and AI | IT PRO

marqvision detects counterfeit products with deep learning and ai | it pro

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MarqVision, the AI-based SaaS company founded by computer scientists and intellectual property (IP) law experts from Harvard University and MIT, recently launched its brand-protection platform to help brands combat counterfeit products online. Using a deep-learning-based image-recognition model to scan through millions of product product listings, MarqVision’s platform can detect those containing products that look similar to the legitimate brand’s products. Its machine learning model then detects potential infringements among those listings and uses a bot-powered reporting system to automatically file take-down requests for listings the brand owner confirms are infringements.The company says brands can regain sales revenue hijacked by counterfeit and knockoff sellers by using the platform. It claims to also help brands protect their reputation while reestablishing customers’ trust.Additionally, MarqVision claims its AI-powered automation technology offers greater efficiency than traditional anti-counterfeiting solutions that often include IP specialists searching for infringements and filing take-down paperwork manually. “The counterfeit market is currently a $1.7 trillion industry, which makes it the largest criminal industry in the world,” said MarqVision CEO and co-founder Mark Lee. “We have pioneered a technology-driven way to solve this serious problem using artificial intelligence. Our beta clients have experienced a 30-fold efficiency increase in their anti-counterfeiting …

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Unraveling Deep Learning Algorithms With Limited Data

unraveling deep learning algorithms with limited data

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The study proposes an alternative repurposing technique for turning the weakness of deep neural networks into strengths.
Deep learning has been an expanse of artificial intelligence, heavily researched by the data scientists in the past few areas. Experts are more curious about supplementing this technology in sectors where human skills perform mundane tasks. As it uses big data, which is garnered from various sources, makes patterns of this collected data and learn to perform a task without any supervision, it becomes data Hungry, which becomes a major challenge when the data is in scarcity. Apart from being hungry, two significant drawbacks presented with deep learning is the opacity and its shallowness. As data sift through many layers between the input and output nodes, identifying the various data points between this layer becomes tricky, which means learning a new algorithm becomes unattainable. Moreover, it becomes difficult for the pre-existing deep. That’s why it becomes imperative for tricking the deep learning models for unraveling new algorithms so that the challenge of scarce data can be countered.

Understanding Deep Learning
Just like the human brain, deep learning utilizes neural networks to process and understand a large amount of data without any supervision. …

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Peter Bart: Does Social Media “Misinformation” Anger You? There’s An AI For That Too

peter bart: does social media “misinformation” anger you? there’s an ai for that too

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The amped-up efforts by Facebook and Twitter to tone down blatant “misinformation” on the campaign trail merits public support. Personally, I find myself trying with limited success to tune out the political noise while sensing that the problem goes beyond that.

The rhetoric of politics overall sounds tired and anachronistic, but then, to my ear, so does much of the dialogue on the popular streamers we binge on. Further, check out the “virtual learning” classes that now pass for “education” and you run into even lazier forms of communication. We all decided the earth was flat even before the new Netflix documentary, titled Social Dilemma, pointed up the random anti-truths directed our way.

So while misinformation is being challenged by the social media monoliths, my techno-nerd friends remind me that the demise of honest communication demands a more drastic approach. Their solution? Get ready to groan — remember, they’re nerds.

Their solution is to alert us to the expanding tools of neuro-symbiotic AI — artificial intelligence. For most of us, AI conjures an old Steven Spielberg movie in which a robotic Haley Joel Osment keeps flunking the tests of his cybertronics instructors. Little wonder the poor kid kept saying “I see …

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Deep Neural Networks Market to Reach USD 5.98 Billion By 2027 | CAGR of 21.4%: Emergen Research

deep neural networks market to reach usd 5.98 billion by 2027 | cagr of 21.4%: emergen research

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VANCOUVER, B.C., Sept. 17, 2020 /PRNewswire/ — The Global Deep Neural Networks Market is projected to reach USD 5.98 billion in 2027. The market is expected to be driven owing to expansion in the big data analytics, emergence of deep learning through neural networks and cognitive analytical procedures in various verticals including IT & telecommunication, BFSI, e-commerce, and healthcare, among others. The rising implementation of the deep neural networks in clinical diagnosis, image & signal analysis and interpretation, and drug & vaccine development, among others, are propelling the market growth broadly. The BFSI sector segment had a mentionable market share due to numerous application areas related to financial analysis, predictive costing, risk investigation, and others.
By eliminating the logical burden from an application developer and disregarding the rule-based preset algorithms, deep neural networks sets an artificial humanlike cognizance which further opens up a wide range of new possibilities to solve many kind of applications without a human inspector. Incorporating neural networks make the computer visions quite easier to work with and extends the limit of what the conventional programming could do.
Request free sample of this research report at: https://www.emergenresearch.com/request-sample/76
Further key findings from the report suggest

Software and applications are the …

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Why Deep Learning DevCon Comes At The Right Time

why deep learning devcon comes at the right time

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The Association of Data Scientists (ADaSci) recently announced Deep Learning DEVCON or DLDC 2020, a two-day virtual conference that aims to bring machine learning and deep learning practitioners and experts from the industry on a single platform to share and discuss recent developments in the field. 

Scheduled for 29th and 30th October, the conference comes at a time when deep learning, a subset of machine learning, has become one of the most advancing technologies in the world. From being used in the fields of natural language processing to making self-driving cars, it has come a long way. As a matter of fact, reports suggest that by 2024, the deep learning market is expected to grow at a CAGR of 25%. Thus, it can easily be established that the advancements in the field of deep learning have just initiated and got a long road ahead.

Also Read: Top 7 Upcoming Deep Learning Conferences To Watch Out For

Deep Learning In The Spotlight With Increased Use Cases

Being a crucial subset of artificial intelligence and machine learning, the advancements in deep learning have increased over the last few years. Thus, it has been explored in various industries, starting from healthcare and eCommerce to advertising and finance, …

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‘Algorithms Facebook uses to detect human faces’ used in farming to help save Great Barrier Reef

‘algorithms facebook uses to detect human faces’ used in farming to help save great barrier reef

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Artificial intelligence that targets weeds may be a game changer for farmers in catchments feeding into the Great Barrier Reef.Key points:A new robotic sprayer is designed to use less herbicides by using a targeted spraying method, rather than wider distribution — meaning less time needed for spraying, at lower cost, and a smaller environmental impact on the reef.James Cook University College of Science and Engineering senior lecturer, Mostafa Rahimi Azghadi, said by spraying a precise amount of herbicide, his project was hoping to reduce the weedkiller’s usage by more than 80 per cent.”When you use less herbicide, not only are you saving the herbicide cost for the farmers, you’re basically having less herbicide running off to the Great Barrier Reef,” Dr Azghadi said.A grant of $400,000 from the Great Barrier Reef Foundation and the Australian Government’s Reef Trust funded the two-year project, which is also testing the run-off water quality at test sites.”Most herbicides are carried in river run-off and have been detected in GBR ecosystems at concentrations high enough to affect organisms,” Dr Azghadi said.”Sugarcane farms are only 1.4 per cent of the GBR catchment area but contribute 95 per cent of the pesticide load draining to …

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StradVision R&D Director to Reveal Insights into Optimizing Deep Neural Networks at 2020 Embedded Vision Summit

stradvision r&d director to reveal insights into optimizing deep neural networks at 2020 embedded vision summit

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SAN JOSE, Calif., Sept. 16, 2020 /PRNewswire/ — StradVision, whose AI-based camera perception software is a leading innovator in Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AVs), will reveal insights into optimizing Deep Neural Networks (DNNs) for multiple processors at the 2020 Embedded Vision Summit. During the “Designing Bespoke DNNs for Target Hardware” session, which will be held at 9:30am Pacific Time on September 17, R&D Director and Co-founder Woonhyun Nam will also elaborate on StradVision’s patent know-how via its deep learning-based SVNet technology.
The presentation marks the sixth time that StradVision has participated in the pre-eminent conference and expo devoted to practical, deployed computer vision and visual AI.
This year’s conference includes speakers from Google, Intel, Samsung, Qualcomm, and LG Electronics, with a keynote speech from Google’s Distinguished Engineer David Patterson, who is also a professor at the University of California, Berkeley, and the Vice-Chair of the RISC-V Foundation.
During his session, Nam will touch on StradVision’s established patents, including their patented DNN-enabled SVNet software, as well as discuss the challenges and opportunities of Deep Neural Networks, including cost-effective techniques to optimize DNNs to better fit different processors while also reducing model size and power consumption. The effort required to transform …

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Deep Learning Courses for NLP Market 2020 World Trends, Segmentation And Opportunities Forecasts To 2025

deep learning courses for nlp market 2020 world trends, segmentation and opportunities forecasts to 2025

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PUNE, MAHARASTRA, INDIA, September 16, 2020 /EINPresswire.com/ —
WiseGuyReports.com Publish A New Market Research Report on –“ Deep Learning Courses for NLP Market 2020 World Trends, Segmentation And Opportunities Forecasts To 2025”.
Deep Learning Courses for NLP Market 2020
Summary: –
The Deep Learning Courses for NLP industry has also suffered a certain impact, but still maintained a relatively optimistic growth, the past four years, Deep Learning Courses for NLP market size to maintain the average annual growth rate of XYZ from XYZ million $ in 2015 to XYZ million $ in 2020, The analysts believe that in the next few years, Deep Learning Courses for NLP market size will be further expanded, we expect that by 2025, The market size of the Deep Learning Courses for NLP will reach XYZ million $.
This Report covers the Major Players’ data, including: shipment, revenue, gross profit, interview record, business distribution etc., these data help the consumer know about the competitors better. This report also covers all the regions and countries of the world, which shows a regional development status, including market size.
Besides, the report also covers segment data, including: type segment, industry segment, channel segment etc. cover different segment market size. Also cover different industries clients’ information, which is very …

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