machine learning


Basketball Goal Detection and RNN

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Now that my machine learning model can detect the different basketball artefacts, we can finally work on some basketball game logic. We can probably detect a goal by adding "region detection boxes" above and below the rim. The "top box" turns red when it detects a ball in its region above the rim. And the "bottom box" shows green when a ball is detected below the rim (where the basketball hoop is). Via the ML model we know with 92% - 94% accuracy where the basketball hoop is located so we can place the red/green boxes automatically on top of the video canvas.


You can have access to 5700 publications from Google Research right now.

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Google Research is a division of Google that focuses on projects that are a little farther out there or require a particular type of domain expertise and they often launch products that make the world a better place. We can divide the research projects into two categories -- short-term, like improving the performance of some already existing product; vs long-term, where they are creating a new product/framework altogether, such as TensorFlow or self-driving cars. Google Research tackles challenges that define the technology of today and tomorrow, and you can have access to its research work as they publish it. Precisely you can access all the 5779 available publications (793 only in 2019) and get inspired, get informed, and learn from it. I'm using this impressive database of research to support me in the writing of my new book: Solving the Greatest Global Challenges with Artificial Intelligence that I plan to launch next March.


Automated Support Interview with Jens Trotzky SAP News

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As we enter a new decade, there is much to reflect on in the area of emerging technologies. It has not even been a full decade since technologies such as artificial intelligence (AI) and machine learning were introduced into the B2B support world, so we know we have only scratched the surface in terms of how these technologies can help improve business processes. We sat down with Jens Trotzky, head of Artificial Intelligence Technology for Customer Success Services at SAP, to discuss what he and his team achieved over the last year in the development of automated support -- and what they are looking forward to in 2020. A: You could say that 2019 was the first chapter of our ever-evolving journey toward an automated service and support function – one that is fueled by the Intelligent Enterprise, for the Intelligent Enterprise, and one that integrates AI and machine learning applications in support. AI did its first real-world heavy lifting for SAP customers in 2019, allowing our team to observe various use cases within automated support and how they've impacted our customers in the early stages.


Validity of machine learning in biology and medicine increased through collaborations across fields of expertise

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Machine learning (ML) has become an essential asset for the life sciences and medicine. We selected 250 articles describing ML applications from 17 journals sampling 26 different fields between 2011 and 2016. Independent evaluation by two readers highlighted three results. First, only half of the articles shared software, 64% shared data and 81% applied any kind of evaluation. Although crucial for ensuring the validity of ML applications, these aspects were met more by publications in lower-ranked journals.


Thank Me Later: How to Organize Your Machine Learning Project

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Checking these items usually means you'll deliver great stuff. What does this have to do with today's newsletter? Well, in case you've been living under a rock, the importance of Machine Learning in our future will rise. Future challenges are complex and only complex systems will solve them. This means the importance of highly organized data and clear workflows for Data Analysts and ML Engineers will rise, also.


Machine Learning Experts Issue Call To Arms For Climate Focus

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Over the past several months, CleanTechnica has been publishing a series of articles on the application of machine learning to clean technologies.


Machine Learning Market to Witness an Outstanding Growth During 2019-2030 – Intel, H2O.ai …

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Market Industry Reports (MIR) has announced the addition of the "Global Machine Learning Market Professional Survey Report 2019-2030" The report …


In 2020, AI will aid administrators and CISOs will refresh internal security

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As healthcare provider organizations confront the steep challenge of securely and efficiently bridging the digital gaps among various technology systems, many are looking to cloud technologies that empower interoperability, marry healthcare information systems with AI, and ensure the privacy and security of patient data. With this in mind, Healthcare IT News turned to Concord Technologies, a cloud fax and document process automation company (it will be in booth 634 at HIMSS20 in March), to look ahead at 2020 and identify three trends with AI-based cloud fax technology. The CAQH Index shows a $9.8 billion savings opportunity for the healthcare industry by reducing the administrative burden found in eligibility and benefit verification, prior authorization, claim submission, coordination of benefits or a crossover claim, claim status inquiry, claim payment, and remittance advice. CAQH is a non-profit alliance of health plans and trade associations developing and leading initiatives designed to positively impact the business of healthcare. In 2020, AI-enabled technologies will transform administrative workflows across digital channels, reducing administrator and clinician burnout and improving overall staff satisfaction, said John Harrison, senior vice president at Concord Technologies.


IBM Watson: AI that's already transforming lives The MSP Hub

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It's time to put AI to work – real work. IBM Watson lives and works in the real world, putting'smart' into operation where it's really needed. To find out more about AI that knows your industry and works with tools you already use, watch the video.


How AI Is Transforming The Modern Healthcare System - Intellectsoft Blog

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Artificial intelligence (AI) in the medical sphere makes use of algorithms and software to approximate human knowledge when analyzing complex information connected to healthcare. AI-based programs are aimed at analyzing how medical prevention or treatment methods are related to the final result. The medical sphere is the main field of investment in AI. Smart medical products, services, and processes are already being developed by companies such as IBM, Google, Apple, and many others. Broadly speaking, AI allows computers to learn from their experiences, adapt to set parameters, and perform tasks that used to be performed only by human beings.