Deep learning has evolved in the past five years from an academic research domain, to being adopted, integrated and leveraged for new dimensions of productivity across multiple industries and use cases, such as medical imaging, surveillance, IoT, chatbots, robotic,s and many more. From NLP to computer vision, deep learning has been breaking the barriers of SOTA algorithms and providing results that were, otherwise, impossible to achieve.

Here at Cloudera, we’ve seen many large organizations struggle to meet ever-changing and ever-growing business demands. We see it everywhere. Traditional on-premise architectures, which create a fixed, finite set of resources, forces every business request for new insight to be a crazy resource balancing act, coupled with long wait times, or a straight-up no, it cannot be done.

As developers, we’ve traditionally rooted out errors in our programs (we’ll call them bugs from now on if that’s ok) by using meaningful log statements. JavaScript has the famous console.log() method for that. But while log statements are good, they are less efficient than a tool that enables you to carry out step-by-step debugging. So in this article, we will learn how to use Google Chrome developer tools (also known as DevTools) to debug any JavaScript application effortlessly.

Kong is excited to participate in Amazon Web Service’s (AWS) APN TV pilot program. This series of demonstration videos from AWS partners focuses on modern application development through the practice of DevOps – a perfect fit for Kong’s service connectivity platform. Microservice architecture involves building software as suites of collaborating services.

Understand the impact of data transfer and egress costs across Microsoft Azure, Amazon Web Services and Google Cloud Platform. One of the questions most frequently asked by cloud-savvy, price-aware customers goes something like this: OK, so we like that your tool makes it easy to integrate our cloud database and storage in our centralized data warehouse, but I know our budget will be scrutinized for total cost of ownership (TCO), including our data egress costs.