Over the past few years, there has been a massive growth in availing the SaaS Development Services, as it has become a feasible choice for businesses that look for convenience and flexibility of software solutions and cloud-based data analysis tools so that they can eliminate the need of installing and running applications on their computer system and data centers. And considering a number of factors like larger bandwidth, faster connections, global digitalization tendencies, and improvement in data processing, we don’t think this growth will stop any time soon.
Enterprises primarily rely on the two domains — artificial intelligence (AI) and machine learning (ML) in order to build and deploy various kinds of models for the smooth operation of their business. However, it requires programmers or data scientists with adequate knowledge of coding, which enterprises often lack. In a bid to ease such woes of the enterprises, tech giants are now open-sourcing their platforms and providing developer tools to ensure businesses can match the ongoing pace without the need for a coding expert.
Our mission is to help define humanity’s place in a world increasingly characterized and driven by algorithms. We do this by creating tangible and applied technical and policy research in the ethical, safe and inclusive development of AI. Our unique advantage in Montreal is that we are situated globally at the leading edge of technical research while leveraging strong Canadian values of diversity and inclusion.
“Treating AI as inherently good overlooks the important research and development needed for ethical, safe and inclusive applications. Poor data, inexplicable code or rushed deployment can easily lead to AI systems that are not worth celebrating.” – Abhishek Gupta, World Economic Forum.
How many engineers does it take to replace a lightbulb? This satirical hypothetical will be used to demonstrate how businesses can optimize their incident response for mission critical tasks.
We’re often found workplace situations that require us to work with others to solve time-sensitive, business-critical, and customer facing issues. Whether a software developer trying to resolve a down website for a eCommerce website or first responders responding to a wildfire incident, time is money (and sometimes human life), thus the quicker the issue is resolved, the happier and sometimes safer your customers will be.
We live in a wonderful era when absolutely anyone can access the latest free satellite images of Earth; it only takes to know where you can find them. Our best seven free GIS data sources list will make it easier to decide which of the available web services has the data you need.
Today we treat you with a list of the top 5 computer vision labs, which we selected for the quality of their research. Ranked in no particular order, these labs conduct top-class, cutting-edge research in computer vision and closely-related areas.
In this article, we provide you with a general overview but we suggest you to discover their research more in-depth by looking at their websites.
We investigate fundamental techniques in Graph Deep Learning, a new framework that combines graph theory and deep neural networks to tackle complex data domains in physical science, natural language processing, computer vision, and combinatorial optimization.
The aim of this research work was to investigate and quantify the risk of fatal and fracture injury for Thoroughbreds participating in flat racing in the US and Canada so that horses at particular risk can be identified and the risk of fatal injury reduced. Risk factors associated with fatalities and fractures were identified and predictive models for both fatalities and fractures were developed and their performance was evaluated. Our analysis was based on 188,269 Thoroughbreds that raced on 89 racecourses reporting injuries to the Equine Injury Database (EID) in the US and Canada from 1st January 2009 to 31st December 2015. This included 2,493,957 race starts and 4,592,162 exercise starts. The race starts reported to the EID represented the starts for 90.0% of all official Thoroughbred racing events in the United States and Canada during the 7-year observation period.
They say it takes a village, but in this digital age it actually just takes a chatroom to instantly connect you with worldwide resources that can turbocharge your career. We’ve combed through our contacts and data to bring you this list of some of the best data science and machine learning slack communities. Go ahead, sign in and spend some time with your peers discussing the issues that are blocking your in your workflow, pitfalls to avoid, or tips to make life easier. Happy slacking!