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Data Science Papers for Spring 2020

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Pain Points, Needs, and Design Opportunities This paper is a study done on the usage of notebooks for data science. It cover a bunch of the negative impacts of using notebooks for data science. Deployment, setup, collaboration, and reliablity are a few of the examples. Quantifying the Carbon Emissions of Machine Learning Training a neural network can take a lot of computer processing power. This processing power comes at a cost to the environment.


Tom Kadala on LinkedIn: Trade Forex differently… using a learning algorithm designed by expert

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Trade Forex differently… using a learning algorithm designed by expert traders. Just over four years ago, we embarked on an ambitious task on the banks of the Thames in London. We decided to rewrite the rules on FOREX trading. Granted there's a lot to choose from, but for the individual who just wants to trade FOREX profitably without having to be glued to their screen all day, we feel we have developed a viable alternative. Our intuitive approach pushes all the technical analysis onto an AI and ML solution called RagingFX.


Accurate and Efficient 3D Motion Tracking Using Deep Learning

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A new sensing method has made tracking movement easier and more efficient. A research group from Tohoku University has captured dexterous 3D motion data from a flexible magnetic flux sensor array, using deep learning and a structure-aware temporal bilateral filter. "We can now track complex motions with higher accuracy," said Yoshifumi Kitamura, co-author of the study. Dexterous 3D motion data can be used for multiple purposes: biologists can use the data to record detailed movements of small animals in their living environments, scientists can track the flow of fluids, and researchers can track finger movements and objects being manipulated by users in virtual reality. Currently, optical cameras are the most prominent method of tracking movements.


Drug Developing Platforms by Artificial Intelligence (AI) Market Competitive Landscape Analysis, Major Regions, Report 2020-2025

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The latest Drug Developing Platforms by Artificial Intelligence (AI) market report offers a detailed analysis of growth driving factors, challenges, and opportunities that will govern the industry expansion in the ensuing years. Besides, it delivers a complete assessment of several industry segments to provide a clear picture of the top revenue prospects of this industry vertical. According to industry analysts, the market is projected to accrue notable gains while recording a CAGR of XX% over the forecast period 2020-2025. Considering the impact of Covid-19, except from healthcare industries, the global health crisis has turned out to be a nightmare for majority of businesses. While some have successfully made changes to their business model or pivoted the entire organization's mission, others continue to face an onslaught of challenges.


Artificial Intelligence (AI) in Insurance Market Size Current and Future Industry Trends, 2020-2025

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The latest Artificial Intelligence (AI) in Insurance market report offers a detailed analysis of growth driving factors, challenges, and opportunities that will govern the industry expansion in the ensuing years. Besides, it delivers a complete assessment of several industry segments to provide a clear picture of the top revenue prospects of this industry vertical. According to industry analysts, the market is projected to accrue notable gains while recording a CAGR of XX% over the forecast period 2020-2025. Considering the impact of Covid-19, except from healthcare industries, the global health crisis has turned out to be a nightmare for majority of businesses. While some have successfully made changes to their business model or pivoted the entire organization's mission, others continue to face an onslaught of challenges.


Hilary Mason - The Future of AI and Machine Learning

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Hilary Mason is the Founder of Fast Forward Labs. She has been involved in the data science space for over a decade. She is a real thought leader in the data space. This keynote was delivered at ODSC East 2020.


How AI is Improving Liquidity in Corporate Credit Markets

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How many traders, desk analysts and quants does it take to price a corporate bond? If you were to answer that question even a few months ago, the number could be as high as a half-dozen. Parties on both sides of the trade would be tasked with checking whether the bond traded recently, analyzing current credit and business conditions, digging into individual bond attributes and taking the pulse of the marketplace to see if the other side of the trade agrees with the price. For a complex trade involving a large portfolio of corporate credits, the process could have taken days. Today, a single trader can do all of that in seconds thanks to advances in machine learning technology which have made it possible to calculate reference pricing in seconds based on dynamic bond market data.


Emotion AI – the future of artificial intelligence?

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Kai works as a sales manager at DMEXCO. Holding a degree in business studies, he had been managing his own start-up for several years. No wonder that at DMEXCO, he is now responsible for everything that has to do with start-ups. Besides his blog stories on the digital start-up scene, Kai's texts focus on future topics such as smart devices, IoT and innovations in the digital economy.


What Is Edge AI and Why Should Enterprises Care?

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The story of the journey of data in the 21st century has been eventful. First, data made the shift from on-premise data centers to the cloud. Now, it is moving towards'edge' points located close to the source of data generation. The dual foundations of Edge AI lie in Edge computing and Artificial Intelligence, two innovative technology trends that have taken the world of business by storm. Edge computing brings processing, computation, and storage of data closer to where it is generated and collected instead of relying on moving it to a remote location such as a cloud.


Global Artificial Intelligence In Military Market 2026 Growth Trends by Manufacturers, Regions, Type and Application, Forecast – The Haitian-Caribbean News Network

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Artificial Intelligence In Military Market Research Report covers the present scenario and the growth prospects of the Keyword Industry for 2020-2026. The report covers the market landscape and its growth prospects over the coming years and discussion of the Leading Companies effective in this market. Artificial Intelligence In Military Market has been prepared based on an in-depth market analysis with inputs from industry experts. To calculate the market size, the report considers the revenue generated from the sales of Keyword globally. The Artificial Intelligence In Military market research study considers the present scenario of the Artificial Intelligence In Military industry and its market dynamics for the period 2020 2026. The report covers both the demand and supply aspects of the market.