Let's cleave the process involved roughly into 2 parts, Before getting started, make sure you have created a virtual environment and installed all dependencies mentioned in previous section.( Flask is a web based microframework. Data scientists prefer flask for their application development as it is lightweight and needs very little code to convert python function into a HTTP endpoint. Assuming, the readers have prior knowledge about libraries and functions used for data analysis and building machine learning models. I will be explaining the elements or functions that are solely used for web app creation from here on.
Amazon Web Services held an online panel discussion Thursday that looked at how the company's cloud infrastructure is supporting the COVID-19 response, from outbreak prediction to vaccine development. The rapid progression from viral outbreak in China to full-blown global pandemic has magnified the role of clinical researchers, biotech companies and drug manufacturers in the global response to the virus. For the key players in this space, the COVID-19 pandemic has become a high stakes data challenge and cloud technology case study. AWS customers BlueDot, Lifebit, AbCellera, Moderna, UC San Diego Health System, and Babylon are using a range of cloud technologies to increase the pace of innovation, accelerate development timelines and help improve outcomes during the COVID-19 pandemic. From cancelled conferences to disrupted supply chains, not a corner of the global economy is immune to the spread of COVID-19.
When I started learning about the semantic web, it was quite foreign territory and the practitioners all seemed to be talking over my head, so when I began to figure it out, I thought it would be valuable to write an introduction for those interested but a little put off. Well it's a whole bunch of things stitched together with many tools and different technologies and standards. Let's start with the problem that the semantic web is trying to solve. Microsoft explained it very well with its Bing commercials on search overload. Not that Bing solves it, but at least Microsoft is good at explaining the problem.
The intersection of the COVID-19 pandemic and analytics has been in focus almost since the pandemic began. Organizations like Johns Hopkins Center for Systems Science and Engineering (CSSE), the New York Times and many governments, including states and municipalities in the US, have been publishing data around a number of indicators, including case counts, hospitalizations, deaths and rates of positive testing. The data sets are downloadable in open formats, and available for self-service analysis. But with so many datasets, new circumstances like in-progress re-openings and new spikes in infection, what's the best way really to make sense of the data? And what other data, not specific to Coronoavirus/COVID-19, might be useful and germane?
NWN, a leading technology-enabled service provider, announced the availability of Officeanywhere, a new integrated suite of managed unified communications and collaboration services that enables digital workplaces to meet current and future business needs. NWN Officeanywhere is powered by technologies from longtime networking leader Cisco, which is also the world's largest enterprise security company and the brand trusted by 95% of the Fortune 500 when it comes to collaboration. NWN offers customers collaboration applications and services that integrate with technology stacks to transform the employee and customer experience. Andrew Gilman, Head of Marketing and Alliances, NWN, said, "Our latest solution aims to help organizations provide the best employee experience -- regardless of where their workforce is situated. During these unprecedented times, organizations need a platform that gives them the flexibility to tackle unforeseen circumstances. Officeanywhere integrates the best-of-breed Cisco Webex cloud voice, video calling, messaging, networking and security into one holistic offering, thereby arming companies with the technology they need to future-proof their communications and never miss a beat."
Melvin Greer is Chief Data Scientist, Americas, Intel Corporation. He is responsible for building Intel's data science platform through graph analytics, machine learning and cognitive computing to accelerate transformation of data into a strategic asset for Public Sector and commercial enterprises. His systems and software engineering experience has resulted in patented inventions in Cloud Computing, Synthetic Biology and IoT Bio-sensors for edge analytics. He significantly advances the body of knowledge in basic research and critical, highly advanced engineering and scientific disciplines. Mr. Greer is a member of the American Association for the Advancement of Science (AAAS) and U.S. National Academy of Science, Engineering and Medicine, GUIRR.
AI/ ML will revolutionize medicine by making diagnosis and treatment more accessible and more effective. FDA has regulated medical software by means of regulation and guidance's for years, however, AI/ML programs fall outside the scope of these regulations and guidance's. This happens because FDA approves the final, validated version of the software. The point of AI/ML is to learn and update following deployment to improve performance. Thus the field version of the software is no longer the validated approved version.
Around the world, researchers in startups, academic institutions and online communities are developing AI models for healthcare. Getting these models from their hard drives and into clinical settings can be challenging, however. Developers need feedback from healthcare practitioners on how their models can be optimized for the real world. So, San Francisco-based AI startup Arterys built a forum for these essential conversations between clinicians and researchers. Called the Arterys Marketplace, and now integrated with the NVIDIA Clara Deploy SDK, the platform makes it easy for researchers to share medical imaging AI models with clinicians, who can try it on their own data.