Systems | Development | Analytics | API | Testing

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Advances in Deep Learning for Image Analysis

Cloudera Fast Forward Labs’ latest applied machine learning research report focuses on advancements in Deep Learning for Image Analysis. Research and commercial interest in deep learning has exploded in the last five years, driving remarkable advancements across applications including medical imaging, autonomous vehicles, news and media (including manipulation), and art.

Creating a successful API Program: Gateway vs API Management

In this video, Google's Irfan Baqui discusses how to have a well thought strategy driving your API program, what a successful API program looks like and how Walgreens, a hundred year old enterprise has been thinking innovatively about their API strategy and their iterative journey through multiple years transforming their business with a successful in the API program.

What to Consider Before Applying CI/CD | A Beginner's Cheat Sheet

Continuous Integration and continuous delivery (CI/CD) is a complex part of any development cycle. It involves continuously integrating code into a shared repository to keep code progression amongst a team of developers running smooth and steady. This helps prevent merging errors, duplicated efforts and promoting collaboration to create a better product. That code is then thoroughly and continuously tested to keep problems from arising.

The first Pay-as-You-Go design environment for accelerating integration projects

The integration landscape is changing. According to Gartner, “Two-thirds of all business leaders believe that their companies must pick up the pace of digital transformation to remain competitive.” One of the byproducts of this increasing pace is the desire to get results quickly. In a cloud-first world, that means expectations are changing for how products are trialed, procured, and billed. People expect things to be simpler, faster, and more intuitive.

Understanding what Machine Learning is and what it can do

As machine learning continues to address common use cases it is crucial to consider what it takes to operationalize your data into a practical, maintainable solution. This is particularly important in order to predict customer behavior more accurately, make more relevant product recommendations, personalize a treatment, or improve the accuracy of research.