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Regularization -- Part 2

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These are the lecture notes for FAU's YouTube Lecture "Deep Learning". This is a full transcript of the lecture video & matching slides. We hope, you enjoy this as much as the videos. Of course, this transcript was created with deep learning techniques largely automatically and only minor manual modifications were performed. If you spot mistakes, please let us know!


5 Ways AI is Transforming the Finance Industry - Maruti Techlabs

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As global technology has evolved over the years, we have moved from television to the internet, and today we are smoothly and gradually adapting Artificial Intelligence. The term AI was first coined by John McCarthy in 1956. It involves a lot of the main things ranging from process automation of robotics to the actual process of robotics. It has become highly popular among large enterprises today owing to the amount of data these companies are dealing in. Increase in the demand for understanding the data patterns has led to the growth in demand of AI.


LinkGeoML – Automatic and accurate interlinking of geospatial data using machine learning

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The automatic and accurate interlinking of geospatial data poses an important scientific challenge, with direct application in several business fields. The major requirement is achieving high accuracy in identifying similar entities within datasets. For example, in a cadastral database, it is crucial that the land parcels, that were gathered from several different databases, are uniquely and clearly identified. In another example, for a geo-marketing company, it is of high importance to be able to accurately cross-reference the location/addresses of customers and companies, so that they are properly targeted. LinkGeoML aims at researching, developing and extending machine learning methods, utilizing the vast amount of available, open geospatial data, in order to implement automated and highly accurate algorithms for interlinking geospatial entities. The proposed methods will implement novel training features, based on domain knowledge and on the analysis of open and proprietary geospatial datasets.


Has AI arrived for financial services?

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When will artificial intelligence really have'arrived'? For a long time, this was a question for philosophers and computer scientists, pondering over whether passing the Turing test truly indicates intelligence, or debating about how broad our definition of artificial intelligence should be. Over the last several years, however, this question has changed considerably: with the advent of consumer AI tools such as virtual assistants and the increasing availability of off-the-shelf solutions offering to bring the power of AI to business operations, the issue has become less philosophical, and much more pragmatic. Now, for business leaders, it is often a matter not of whether to respond to the arrival of AI, but of how to respond to the arrival of AI. The promise is, of course, huge.


Cherre and Upsuite Announce Partnership

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"Coworking and flexible Office is one of the most dynamic asset classes in commercial real estate right now, and we think Cherre is the right partner to help institutional owners, investors, and other stakeholders see the past, present and future of this asset class," said Ben Wright, Founder and CEO of Upsuite. Cherre seamlessly connects disparate real estate data into a single-source of truth, empowering companies to instantly explore all their connected data. Cherre has the largest real estate knowledge graph in the world and enables customers to uncover granular insights, automate workflows, and build models and visualizations. "Property owners need comprehensive data to make more informed investment and business decisions," said L.D. Salmanson, CEO and Co-Founder of Cherre. "Analyzing coworking and flex space data alongside other connected data sources will enable better trend and market analysis for decision making."


How To Improve Channel Sales With AI-Based Knowledge Sharing Networks

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Bottom Line: Knowledge-sharing networks have been improving supply chain collaboration for decades; it's time to enhance them with AI and extend them to resellers to revolutionize channel selling with more insights. Add to that the complexity of selling CPQ and product configurations through channels, and the value of using AI to improve knowledge sharing networks becomes a compelling business case. Automotive, consumer electronics, high tech, and industrial products manufacturers are combining IoT sensors, microcontrollers, and modular designs to sell channel-configurable smart vehicles and products. AI-based knowledge-sharing networks are crucial to the success of their next-generation products. Likewise, to sell to any of these manufacturers, suppliers need to be pursuing the same strategy.


AI is Transforming Digital Marketing Landscape in 2020 - The Next Scoop

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Understanding text, images, and sounds is not a uniquely human prerogative anymore. Artificial intelligence is transforming virtually every business. AI's ability to derive data-driven insights is paving the road to better digital marketing. From the vast data analysis, marketers gain valuable consumer insights and change how they connect brands with their audiences. Why artificial intelligence cannot be separated from digital marketing anymore?


How Marketing AI Will Transform Your Lead Generation (and Conversion)

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Artificial intelligence is about to change lead generation and conversion as you know it. In the process, it'll have a transformative impact on companies and careers. AI is a blanket term that covers several different technologies. You might have heard of some of them, like machine learning, computer vision, and natural language processing. Even if you don't know much about it, though, you probably use AI-powered technology dozens or hundreds of times per day.


Automated histologic diagnosis of CNS tumors with machine learning

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A new mass discovered in the CNS is a common reason for referral to a neurosurgeon. CNS masses are typically discovered on MRI or computed tomography (CT) scans after a patient presents with new neurologic symptoms. Presenting symptoms depend on the location of the tumor and can include headaches, seizures, difficulty expressing or comprehending language, weakness affecting extremities, sensory changes, bowel or bladder dysfunction, gait and balance changes, vision changes, hearing loss and endocrine dysfunction. A mass in the CNS has a broad differential diagnosis, including tumor, infection, inflammatory or demyelinating process, infarct, hemorrhage, vascular malformation and radiation treatment effect. The most likely diagnoses can be narrowed based on patient demographics, medical history, imaging characteristics and adjunctive laboratory studies. However, accurate histopathologic interpretation of tissue obtained at the time of surgery is frequently required to make a diagnosis and guide intraoperative decision making. Over half of CNS tumors in adults are metastases from systemic cancer originating elsewhere in the body [1]. An estimated 9.6% of adults with lung cancer, melanoma, breast cancer, renal cell carcinoma and colorectal cancer have brain metastases [2].


Causal AI & Bayesian Networks

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We are all familiar with the dictum that "correlation does not imply causation". Furthermore, given a data file with samples of two variables x and z, we all know how to calculate the correlation between x and z. But it's only an elite minority, the few, the proud, the Bayesian Network aficionados, that know how to calculate the causal connection between x and z. Neural Net aficionados are incapable of doing this. Their Neural nets are just too wimpy to cut it.