Author Archives: 365Data Science

Lessons on AI from the author of Own the AI Revolution. Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/artificial-intelligence-in-business-with-neil-sahota-d9ce5f209c5b?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/artificial-intelligence-and-business-with-neil-sahota

AI tools and services are expanding at a rapid clip, and keeping a handle on this evolving ecosystem is crucial for the success of your AI projects. This framework will help you build your technical stack to deploy AI projects faster and at scale. Originally from KDnuggets https://ift.tt/3f60z7n source https://365datascience.weebly.com/the-best-data-science-blog-2020/demystifying-the-ai-infrastructure-stack

This article demonstrates how building a smarter API serving Deep Learning models minimizes the response time. Originally from KDnuggets https://ift.tt/2WuWst5 source https://365datascience.weebly.com/the-best-data-science-blog-2020/optimize-response-time-of-your-machine-learning-api-in-production

This post explains using a pre-trained GAN to generate human faces, and discusses the most common generative pitfalls associated with doing so. Originally from KDnuggets https://ift.tt/2y62xUB source https://365datascience.weebly.com/the-best-data-science-blog-2020/which-face-is-real-applying-stylegan-to-create-fake-people

Here is an overview of another great natural language processing resource, this time from Microsoft, which demonstrates best practices and implementation guidelines for a variety of tasks and scenarios. Originally from KDnuggets https://ift.tt/3bXbPRe source https://365datascience.weebly.com/the-best-data-science-blog-2020/natural-language-processing-recipes-best-practices-and-examples

This year’s KDD Cup features four distinct tracks that welcome participants to tackle challenges in e-commerce, generative adversarial networks, automatic graph representation learning (AutoGraph) and mobility-on-demand (MoD) platforms. Winners will be recognized at KDD 2020, the leading interdisciplinary conference in data science, in San Diego on August 23-27, 2020. Originally from KDnuggets https://ift.tt/3f5Hpym source https://365datascience.weebly.com/the-best-data-science-blog-2020/kdd-2020-invites-top-data-scientists-to-compete-in-24th-annual-kdd-cup

You walk down one aisle of the grocery store to get your favorite cereal. On the dairy aisle, someone sick from COVID-19 coughs. Did your decision to grab your cereal before your milk possibly keep you healthy? How can these unpredictable, near-random choices be included in complex models? Originally from KDnuggets https://ift.tt/2VNHnDE source https://365datascience.weebly.com/the-best-data-science-blog-2020/outbreak-analytics-data-science-strategies-for-a-novel-problem

Source Thank you for stopping by! This is the first part, a kind of introductory story to a series where I will be describing my company’s efforts and progress in bringing AI (Artificial Intelligence) to the world of CFD (Computational Fluid Dynamics). We believe it will be a complete game-changer for many industries, not onlyContinue reading “AI for CFD: Intro (part 1)”

Source While the COVID-19 threat continues to grip the world and people are falling prey to this invisible enemy, AI has come up with a tool that will help in finding out the severity of the patients suffering from this disease. Artificial Intelligence has been around for quite some time, but it’s only recently thatContinue reading “How AI Can Determine Which Coronavirus Patients Require Hospitalization”

Face recognition, or facial recognition, is one of the largest areas of research within computer vision. We can now use face recognition… Continue reading on Becoming Human: Artificial Intelligence Magazine » Via https://becominghuman.ai/5-papers-on-face-recognition-every-data-scientist-should-read-76a1fc55c573?source=rss—-5e5bef33608a—4 source https://365datascience.weebly.com/the-best-data-science-blog-2020/5-papers-on-face-recognition-every-data-scientist-should-read