Systems | Development | Analytics | API | Testing

The design and training of neural networks are still challenging and unpredictable procedures. The difficulty of tuning these models makes training and reproducing more of an art than a science, based on the researcher’s knowledge and experience. One of the reasons for this difficulty is that the training procedure of machine learning models includes multiple hyperparameters that affect how the training process fits the model to the data.

Data Discovery and Exploration (DDE) was recently released in tech preview in Cloudera Data Platform in public cloud. In this blog we will go through the process of indexing data from S3 into Solr in DDE with the help of NiFi in Data Flow. The scenario is the same as it was in the previous blog but the ingest pipeline differs. Spark as the ingest pipeline tool for Search (i.e.

Much has been written on the growth of machine learning and its impact on almost every industry. As businesses continue to evolve and digitally transform, it’s become an imperative for businesses to include AI and ML in their strategic plans in order to remain competitive. In Competing in the Age of AI, Harvard professors Marco Iansiti and Karim R. Lakhani illustrate how this can be confounding for CEOs, especially in the face of AI-powered competition.

For example, let’s say that an app that we’re working on supports multiple themes, and that we’re keeping track of the user’s currently selected theme (and other user-configurable settings) through a SettingsController — which in turn uses Foundation’s UserDefaults API to persist those settings, like this.

This quarter we’ve been working on many improvements that will make your life easier when catching those sneaky bugs, and expand Bugfender’s capabilities with some of the most requested features: We hope you find all these updates useful!