KDnuggets™ News 18:n03, Jan 17: Top 10 TED Talks on Data Science, Machine Learning; How Docker Can Help You Become A More Effective Data Scientist

[unable to retrieve full-text content]Also A Primer on Web Scraping in R; Elasticsearch for Dummies; Generative Adversarial Networks, an overview,
Original Post: KDnuggets™ News 18:n03, Jan 17: Top 10 TED Talks on Data Science, Machine Learning; How Docker Can Help You Become A More Effective Data Scientist

Local AI Inferencing Will Become Standard In Edge Applications In 2018

[unable to retrieve full-text content]Edge-based inferencing will become a foundation of all AI-infused applications in the Internet of Things and People and the majority of new IoT&P application-development projects will involve building the AI-driven smarts for deployment to edge devices for various levels of local sensor-driven inferencing.
Original Post: Local AI Inferencing Will Become Standard In Edge Applications In 2018

Services and tools for building intelligent R applications in the cloud

by Le Zhang (Data Scientist, Microsoft) and Graham Williams (Director of Data Science, Microsoft) As an in-memory application, R is sometimes thought to be constrained in performance or scalability for enterprise-grade applications. But by deploying R in a high-performance cloud environment, and by leveraging the scale of parallel architectures and dedicated big-data technologies, you can build applications using R that provide the necessary computational efficiency, scale, and cost-effectiveness. We identify four application areas and associated applications and Azure services that you can use to deploy R in enterprise applications. They cover the tasks required to prototype, build, and operationalize an enterprise-level data science and AI solution. In each of the four, there are R packages and tools specifically for accelerating the development of desirable analytics. Below is a brief introduction of each. Cloud resource management and operation Cloud computing instances…
Original Post: Services and tools for building intelligent R applications in the cloud

AI and Deep Learning in Healthcare – save with code KDnuggets

[unable to retrieve full-text content]This year, RE-WORK will be continuing the Global Healthcare Series, focusing on the AI and deep learning tools and techniques set to revolutionise healthcare applications, medicine & diagnostics. Save an additional 20% on already discounted passes with the code: KDNUGGETS
Original Post: AI and Deep Learning in Healthcare – save with code KDnuggets

Democratizing Artificial Intelligence, Deep Learning, Machine Learning with Dell EMC Ready Solutions

[unable to retrieve full-text content]Democratization is defined as the action/development of making something accessible to everyone, to the “common masses.” AI | ML | DL technology stacks are complicated systems to tune and maintain, expertise is limited, and one minimal change of the stack can lead to failure.
Original Post: Democratizing Artificial Intelligence, Deep Learning, Machine Learning with Dell EMC Ready Solutions

KDnuggets™ News 18:n02, Jan 10: Quantum Machine Learning; AI & Blockchain Convergence; Building a Successful Analytics Dept

[unable to retrieve full-text content]Quantum Machine Learning: An Overview; How to build a Successful Advanced Analytics Department; Top Data Science, Machine Learning Courses from Udemy; Supercharging Visualization with Apache Arrow; The Convergence of AI and Blockchain: What’s the deal?
Original Post: KDnuggets™ News 18:n02, Jan 10: Quantum Machine Learning; AI & Blockchain Convergence; Building a Successful Analytics Dept